阅读说明：本技术 非侵入性连续血糖监测仪 (Non-invasive continuous blood glucose monitor ) 是由 M·诺姆瓦尔 S·考克斯 T·特尔弗 D·王 于 2021-01-29 设计创作，主要内容包括：本文提供了一种用于测量受试者,优选人类受试者的葡萄糖水平(即,浓度)的非侵入性设备。本发明涉及用于测量血糖浓度/水平的可穿戴设备、套件及其方法。本发明的非侵入性设备可用作智能手环、指环、手环、手表等可穿戴设备,通过测量生物阻抗数据来监测糖尿病患者的血糖水平,而不会因手指刺破而感到不适和压力。(Provided herein is a non-invasive device for measuring glucose levels (i.e., concentrations) in a subject, preferably a human subject. The invention relates to a wearable device, a kit and a method thereof for measuring blood glucose concentration/level. The non-invasive device of the present invention can be used as a wearable device such as a smart bracelet, ring, bracelet, watch, etc. to monitor blood glucose levels of a diabetic patient by measuring bioimpedance data without discomfort and stress from finger pricks.)

1. A non-invasive device for determining blood glucose concentration in a subject, the device comprising:

at least two electrodes for contacting the skin of the subject and adapted to be connected to a receiver to measure an impedance signal; and

a housing adapted to receive the electrode; wherein the electrodes are configured such that an electrical current is passed through a portion of the subject in use.

2. The non-invasive apparatus of claim 1, further comprising a probe.

3. A non-invasive device for determining blood glucose concentration in a subject, the device comprising:

at least two electrodes for contacting the skin of the subject and adapted to be connected to a receiver to measure an impedance signal;

a housing adapted to receive an electrode; and

a probe for measuring at least one additional physiological parameter.

4. The non-invasive device according to any one of claims 1 to 3, wherein a single electrode can inject current and measure voltage.

5. The non-invasive device of any one of claims 1 to 3, wherein the electrodes independently inject current and measure voltage.

6. The non-invasive apparatus according to any one of claims 1 to 5, wherein the apparatus comprises four electrodes.

7. The non-invasive device of claim 6, wherein two electrodes inject current and two electrodes measure voltage.

8. The non-invasive apparatus according to any one of claims 1 to 7, wherein the apparatus comprises at least two component apparatuses.

9. The non-invasive device according to any one of claims 1 to 8, wherein the electrodes are configured to be radially spaced about greater than about 20 ° to less than about 180 ° about a reference point.

10. The non-invasive device of any one of claims 1 to 8, wherein the electrodes are substantially opposite one another.

11. The non-invasive device according to any one of claims 1 to 8, wherein the two electrodes are substantially opposite each other.

12. The non-invasive device according to claim 11, further comprising two additional electrodes configured to be radially spaced relative to the two electrodes by about greater than about 5 ° to less than about 80 °.

13. The non-invasive device of claim 12, wherein the two additional electrodes are configured to be radially spaced relative to the two electrodes by about more than about 30 ° to less than about 60 °.

14. The non-invasive apparatus according to any one of claims 11 to 13, wherein the two electrodes are current injection electrodes.

15. The non-invasive apparatus according to any one of claims 11 to 14, wherein the two additional electrodes are voltage measurement electrodes.

16. The non-invasive device of any one of claims 1 to 15, wherein the electrodes are substantially square.

17. The non-invasive apparatus according to any one of claims 14 to 16, wherein the voltage measurement electrodes are spaced to provide a gap of about 0.2mm to about 1cm relative to the current injection electrodes.

18. The non-invasive apparatus according to claim 17, wherein the voltage measurement electrodes are spaced to provide a gap of about 0.5mm to about 1.5mm relative to the current injection electrodes.

19. The non-invasive device according to any one of claims 1 to 18, wherein the electrodes are made of a metal or a salt thereof, a metal alloy or a conductive polymer.

20. The non-invasive device according to any one of claims 1 to 18, wherein the electrodes are made of a material selected from the group consisting of: electroceramics, copper, aluminum, platinum, titanium, gold, silver, iron, steel, stainless steel, brass, bronze, nickel, silver/silver chloride, conductive rubber, conductive carbon, and combinations thereof.

21. The non-invasive device of any one of claims 1 to 20, wherein the electrode comprises a coating.

22. The non-invasive device of claim 21, wherein the coating has a thickness of about 10nm to 500 microns.

23. The non-invasive device of any one of claims 1 to 22, wherein the surface area of the electrodes is about 2 to 100mm²。

24. The non-invasive device according to any one of claims 1 to 23, wherein the housing is made of a material selected from the group consisting of: ceramic, stone, leather, silicone rubber, copper, aluminum, platinum, titanium, gold, silver, iron, steel, stainless steel, brass, bronze, nickel, wood, bone, polymers, and combinations thereof.

25. The non-invasive apparatus according to any one of claims 1 to 24, comprising an adjustable electrode contact mechanism.

26. The non-invasive apparatus according to any one of claims 1 to 25, further comprising a notification indicator.

27. A non-invasive device according to any one of claims 1 to 26, wherein the receiver is integral with the device.

28. The non-invasive device according to any one of claims 1 to 27, wherein the receiver is external to the non-invasive device.

29. The non-invasive apparatus according to any one of claims 1 to 28, wherein the apparatus includes a faraday shield.

30. The non-invasive device according to any one of claims 1 to 29, wherein the device is integrally formed with, attached to or at least partially surrounding or enclosing a third party device.

31. The non-invasive device according to any one of claims 1 to 30, wherein the device is a smart watch, belt, band, bracelet, ring, or clip.

32. The non-invasive apparatus according to any one of claims 1 to 31, further comprising a communication apparatus.

33. A method for non-invasively determining a subject's blood glucose concentration, the method comprising the steps of:

measuring impedance through a portion of the subject using at least two electrodes in conductive contact with the subject's skin; and

determining a blood glucose amount of the subject based on the measured impedance, wherein the at least two electrodes are in a configuration that passes current through the portion of the subject.

34. The method of claim 33, further comprising measuring at least one additional physiological parameter for the subject.

35. A method for non-invasively determining a subject's blood glucose concentration, the method comprising the steps of:

measuring impedance through a portion of the subject using at least two electrodes in conductive contact with the subject's skin;

determining the subject's blood glucose based on the measured impedance; and

measuring at least one additional physiological parameter of the subject.

36. The method of any of claims 33 to 35, wherein the impedance is measured at a plurality of frequencies.

37. The method of any one of claims 33 to 36, wherein the measuring is performed in a frequency range of about 0.1Hz to about 1 MHz.

38. The method of any one of claims 33 to 37, wherein the method uses an alternating current.

39. The method of any one of claims 33 to 38, wherein the method uses direct current.

40. The method of any one of claims 33 to 39, wherein the portion of the subject is selected from the group consisting of: fingers, ears, waist, legs, arms, wrists, and combinations thereof.

41. The method of any one of claims 33 to 40, wherein the method is continuous.

42. The method of any one of claims 33 to 41, wherein the method is performed at intervals.

43. The method of any one of claims 34 to 42, wherein the physiological parameter is selected from the group consisting of: body fat, muscle mass, body composition, body temperature, skin pH, skin temperature, blood pressure, heart rate, and combinations thereof.

44. A method according to any one of claims 33 to 43, wherein the method includes a pre-treatment step.

45. The method of claim 44, wherein the pre-treatment step involves shaving and/or cleansing the skin.

46. The method of any one of claims 33 to 45, wherein the conductive layer is applied to the skin.

47. The method of claim 46, wherein the conductive layer is in the form of a gel, paste, ointment, or cream.

48. The method of any one of claims 33 to 47, further comprising using an artificial neural network.

49. A kit, comprising:

at least two electrodes adapted to be connected to a receiver to measure an impedance signal; and

a housing adapted to receive the electrode.

50. The kit of claim 49, further comprising a receiver.

51. The kit of claim 50, wherein the receiver is an electrochemical impedance spectroscopy device.

52. The kit of any one of claims 49-51, further comprising an insulin pump.

Technical Field

The present invention relates to a non-invasive device for measuring glucose levels (i.e. concentrations) in a subject, preferably a human subject.

In particular, the present disclosure relates to wearable devices, kits and methods thereof for measuring blood glucose concentrations/levels. These non-invasive devices may be used as wearable devices, such as smartband or watches, to monitor blood glucose levels in diabetic patients by measuring bioimpedance data without discomfort and stress from finger pricks. It should be understood, however, that the invention is not limited to this particular field of use.

Background

The following discussion of the prior art is provided to place the present invention in a suitable technical context and enable its advantages to be more fully understood. It should be understood, however, that any discussion of the prior art throughout the specification should not be considered as an explicit or implicit acknowledgement that such prior art is widely known or forms part of the common general knowledge in the field.

Over the past 30 years, the rate of obesity has increased dramatically due to the increase in processed foods and the increase in sugar levels in beverages. The obesity rate of adults has increased by more than 25% globally, and that of children and young adults has increased even by nearly 50%. To date, the number of overweight and obese people worldwide has increased from about 8 billion in 1980 to over 20 billion in 2013. Currently, there are over 6 billion obese people worldwide.

Studies have shown that obesity can increase the likelihood of developing diabetes mellitus (diabetes/diabetes mellitis). Diabetes mellitus is a chronic disease characterized by high glucose levels in the blood. Blood glucose levels are controlled by insulin, a hormone produced by the pancreas. Diabetes occurs when the pancreas (i) fails to produce enough insulin, (ii) the body is resistant to insulin, or (iii) both. Two common forms of diabetes are:

type 1 diabetes: an autoimmune disease in which the body's immune system attacks the insulin producing cells of the pancreas. Type 1 diabetes is the result of the failure of the pancreas to produce sufficient insulin due to beta cell loss. Type 1 diabetics cannot produce insulin and require lifelong injections of insulin to survive; and

type 2 diabetes: one cell is unable to respond properly to insulin, usually beginning with a disorder of insulin resistance. In some cases or as the disease progresses, insulin deficiency may occur. Type 2 diabetes is often associated with genetic and lifestyle risk factors including poor diet, insufficient physical activity, and overweight or obesity.

Diabetic patients in need of treatment attempt to maintain blood glucose levels within a specific range prescribed by health professionals. Currently, the only reliable way to self-measure blood glucose levels is to use a conventional blood glucose monitor. However, conventional blood glucose monitors are invasive, inconvenient, painful and cause discomfort. To monitor blood glucose concentration, a user pricks their finger with a lancet and then applies a drop of blood to a blood glucose test strip. The strip is then inserted into a meter, which reads the strip and displays the blood glucose concentration.

Non-invasive methods for measuring blood glucose concentration in a subject have been developed. These methods typically measure the impedance of the skin tissue. However, commercial applications of bioimpedance measurements of blood glucose levels are limited.

PCT/US1998/002037 discloses a method and apparatus for non-invasively determining the glucose level, typically blood glucose level, in a body fluid of a subject. The impedance of the skin tissue is measured and this measurement is used together with the impedance measurement previously associated with the directly determined glucose level to determine the glucose level from the newly measured impedance.

PCT/RU2013/000144 discloses a method for measuring impedance of a skin tissue area of a human body at high and low frequencies by means of electrodes fixed to the human body, and measuring a blood glucose concentration by measuring a volume value of an extracellular fluid.

However, the methods and devices discussed above are limited to measuring bio-impedance on skin tissue. Therefore, the reproducibility, repeatability and accuracy of blood glucose measurements of bio-impedance based devices is poor, which is a serious drawback; incorrect measurement of glucose concentration in blood can have serious health consequences for diabetics.

It is an object of the present invention to overcome or ameliorate one or more of the disadvantages of the prior art, or at least to provide a useful alternative.

It is an object of at least one preferred form of the invention to provide a method or apparatus by which a subject's blood glucose concentration can be accurately measured.

Although the invention will be described with reference to specific examples, it will be appreciated by those skilled in the art that the invention may be embodied in many other forms.

Summary of The Invention

Bioelectrical impedance (bioimpedance) measurements have been used to measure physiological parameters in biological applications to characterize cells. These measurements include measuring body composition (e.g., body fat and muscle mass), whole body moisture, and other applications. Bioimpedance measurements have also been used in disease diagnostic applications.

However, bio-impedance measurements have limited application in measuring blood glucose concentrations. Indeed, applicants believe that there are no commercial products currently on the market that use impedance to measure the subject's blood glucose concentration.

The development of non-invasive blood glucose devices using impedance measurements has been challenging because the measurements are typically of poor quality or weak signals, resulting in poor reproducibility, repeatability, and accuracy of the blood glucose concentration measurements. Therefore, developing a suitable non-invasive blood glucose device using impedance for commercialization remains a significant challenge. This is because the electrodes in these devices are limited to measuring impedance on the skin tissue, which can result in poor quality or weak signals.

According to one aspect, the present invention provides a non-invasive device for determining the blood glucose concentration of a subject, the device comprising: at least two electrodes for contacting the skin of the subject and adapted to be connected to a receiver to measure an impedance signal; and a housing adapted to receive the electrode; wherein the electrodes are configured to pass an electrical current through a portion of the subject in use.

According to another aspect, the present invention provides a non-invasive device for determining the blood glucose concentration of a subject, the device comprising: at least two electrodes for contacting the skin of the subject and adapted to be connected to a receiver to measure an impedance signal; a housing adapted to receive an electrode; and a probe for measuring at least one additional physiological parameter.

The applicant has surprisingly found that by placing the electrodes in a configuration that provides an electrical current to pass through a part of the body rather than just on the skin surface, a device is provided that can measure high quality signals to enable reproducible, repeatable and accurate blood glucose concentration measurements.

Without being bound by any one theory, applicants have surprisingly found that electrical current can pass through a portion of the body (e.g., a finger) through at least one of the dermis layer, the fat layer, the muscle, the bone, and the like. The current may be passed through different parts of the body, for example, part of the current may be passed through the dermis layer, the fat layer, the bodily fluids, and combinations thereof. Furthermore, currents of different frequencies will have different path combinations. In some embodiments, the non-invasive device comprises three, four, five, six, seven, eight, nine, or ten electrodes. In a preferred embodiment, the non-invasive device comprises four electrodes.

In certain embodiments, when the non-invasive device comprises two or three electrodes, there may be a possibility of the positive and negative current injection electrodes and the voltage measurement electrode being shorted in some embodiments. However, in a four-electrode non-invasive device, since the current injection electrode and the voltage measurement electrode are independent (separated), the risk of short circuits can be reduced or prevented. In this preferred embodiment, no load effect is created on the electrodes, since no current passes through the voltage measuring electrodes, which would otherwise result from current injection into the electrodes.

It will be appreciated by those skilled in the art that a non-invasive device comprising two or three electrodes may be used in the present invention as it may still function equivalently to the preferred four-electrode system, however, due to the more complex biological system (e.g. for measuring blood glucose levels), a two or three electrode device may underestimate or overestimate the measurement as the electrodes may be current injection electrodes and/or voltage measurement electrodes. Four electrodes can prevent any electrical problems (short circuits) and provide higher sensitivity, since each electrode can independently be a separate current injection electrode (i-and i +) and voltage measurement electrode (v-and v +). Thus, preferred embodiment devices using four electrodes may provide greater sensitivity and reduce or prevent shorting.

For example, if the device contains two or three electrodes, the i-, i +, v-, and v + electrodes/probes are not uniformly distributed. In embodiments containing two or three electrodes, the four contacts (i-, i +, v-, and v +) would have to be distributed over multiple contacts/electrodes, which may increase the likelihood of shorting the device, as the probes may be at the same terminal.

One inherent characteristic of bioimpedance is sensitivity. A higher level of sensitivity can be obtained using a four electrode device. The inventors have surprisingly found that four electrodes improve the effectiveness of measuring bio-impedance from a narrow specific range in a biological system compared to a two or three electrode device.

In some embodiments, a single electrode may inject a current into the skin of a subject and measure a voltage. In other embodiments, the electrodes independently inject current and measure voltage in respective circuits. In a preferred embodiment, the non-invasive device comprises a stimulation electrode and a sensing electrode. I.e. one electrode will inject a current and the other electrode will measure a voltage response. For example, for a non-invasive device containing four electrodes, two electrodes may inject current and two electrodes may measure voltage.

It has surprisingly been found that the benefit of separating the current injection (stimulation) electrode from the voltage measurement (sensing) electrode when making an impedance measurement is that any loading or polarization of the current injection electrode does not affect the voltage measurement performance. In these embodiments, no current should flow into or out of the voltage sensing path, as only the voltage (or potential) response of the subject due to the stimulation current should be sensed.

In some embodiments, the non-invasive device comprises at least two component devices, such that each component device comprises at least one electrode. In these embodiments, one component device comprising at least one electrode may be a stimulation device, while another component device comprising at least one electrode may be a sensing device.

It will be appreciated that the electrodes may be placed in any suitable configuration provided to pass an electrical current through a portion of the subject. In some embodiments, the electrodes are substantially uniformly distributed over the portion of the subject. In some embodiments, the electrodes are substantially opposite each other. In some embodiments, the electrodes are configured to be radially spaced apart by about greater than about 20 ° to less than about 180 °, greater than about 30 ° to less than about 180 °, about 40 ° to less than about 180 °, about 50 ° to less than about 180 °, about 70 ° to less than about 180 °, about 90 ° to less than about 180 °, about 120 ° to less than about 180 °, about 150 ° to less than about 180 °. In some embodiments, the electrodes are configured to be radially spaced apart less than about 180 °, less than about 150 °, less than about 120 °, less than about 90 °, less than about 45 °, less than about 30 ° about the reference point. In some embodiments, the current injection (stimulation) electrode is substantially opposite the voltage measurement (sensing) electrode. In some embodiments, the positive electrode is substantially opposite the negative electrode.

In a preferred embodiment, the device comprises four electrodes. In this embodiment, the two electrodes are substantially opposite each other along the axis. For example, when the device is in the form of a ring, the two electrodes are spaced approximately 180 ° from each other. In this embodiment, each of the additional electrodes (i.e., the additional two electrodes) is configured to be radially spaced relative to each electrode by about greater than about 5 ° to less than about 80 °, about greater than about 5 ° to less than about 60 °, about greater than about 5 ° to less than about 50 °, about greater than about 20 ° to less than about 40 °, preferably about 30 ° or about 60 °. In a preferred embodiment, each of the additional electrodes (i.e., the additional two electrodes) is configured to be radially spaced relative to each electrode by about greater than about 5 ° to less than about 80 °, about greater than about 5 ° to less than about 60 °, about greater than about 5 ° to less than about 50 °, about greater than about 20 ° to less than about 40 °, preferably about 30 °, and the additional electrodes are substantially opposite one another. It will be appreciated by those skilled in the art that the term "substantially opposite" means that the centroids of the electrodes and/or additional electrodes are configured at about 180 ° to each other, however, the contact angle of the electrode surfaces may be any suitable angle.

In certain embodiments, the two electrodes are current injection electrodes and the two additional electrodes are voltage measurement electrodes. In other embodiments, the two electrodes are voltage measurement electrodes and the two additional electrodes are current injection electrodes. In certain embodiments, at least one of the electrodes is a current injection electrode and at least one of the additional electrodes is a voltage measurement electrode.

The inventors have found that a four-electrode non-invasive device is more suitable for measuring bio-impedance. Prior to the present application, it was generally believed that measuring bio-impedance using a four electrode device was error prone compared to one or two electrode configurations.

The inventors have also found that the use of four electrodes avoids common mode voltages, thereby reducing or preventing electrode polarization effects that would be experienced in a two electrode system. Two-electrode systems are the most common systems commonly used for bioimpedance measurements.

In some embodiments, the voltage measuring electrodes of the present invention may be spaced to provide a gap of about 0.2mm to about 1cm, about 0.2mm to about 10mm, about 0.2mm to about 3mm, about 0.2mm to about 2cm, about 0.5mm to about 1.5mm, preferably about 1mm, relative to the current injecting electrodes.

One skilled in the art will appreciate that one or more of the electrodes may take any geometry or size depending on the optimized impedance signal. The electrodes may take any suitable shape and may be, for example, circular, square, triangular, diamond-shaped, trapezoidal, rectangular, pentagonal, hexagonal, octagonal, or irregularly shaped. In a preferred embodiment, the electrodes are substantially square, preferably square. The inventors have surprisingly found that a substantially square electrode reduces the impedance at the skin-electrode interface and is more sensitive to changes in bio-impedance than a circular electrode having a similar cross-sectional surface area.

It should be appreciated that the electrodes may be made of any suitable conductive material. In some embodiments, the electrodes are made of a metal or salt thereof, a metal alloy, or a conductive polymer. In some embodiments, the electrode is made of a material selected from the group consisting of: electroceramic, copper, aluminum, platinum, titanium, gold, silver, iron, steel, stainless steel, brass, bronze, nickel, silver/silver chloride, conductive rubber, conductive carbon (such as graphite, graphene and reduced graphene oxide), and combinations thereof. In a preferred embodiment, the electrode is a gold electrode or a silver/silver chloride electrode. In some embodiments, the electrode is a patch.

In some embodiments, the electrode may comprise a coating of another conductive material. In these embodiments, the use of less expensive electrodes (such as aluminum, stainless steel, and copper) can be used in conjunction with a coating of a desired conductive material (e.g., gold) to improve the conductive contact between the subject's skin and the electrodes. The applicant has surprisingly found that the use of gold or gold-plated electrodes improves the signal quality of the impedance measurement.

In some embodiments, the coating is made of a metal or salt thereof, a metal alloy, or a conductive polymer. In some embodiments, the coating is made of a material selected from the group consisting of: electroceramics, copper, aluminum, platinum, titanium, gold, silver, iron, steel, stainless steel, brass, bronze, nickel, silver/silver chloride, conductive rubber, conductive carbon, and combinations thereof. In a preferred embodiment, the coating is a gold coating.

In certain embodiments, the gold or gold-plated electrode is at least about 99%, at least about 99.5%, at least about 99.9%, at least about 99.99%, or at least about 99.999% gold. In a preferred embodiment, the gold or gold-plated electrode is at least about 99.99% gold.

In certain embodiments, the coating of the electrode is gold or gold-plated, and is at least about 99%, at least about 99.5%, at least about 99.9%, at least about 99.99%, or at least about 99.999% gold. In a preferred embodiment, the coating of the electrode is at least about 99.99% gold.

The inventors have surprisingly found that the use of gold or gold-plated electrodes may provide a minimum impedance at the skin-electrode interface for monitoring biometric information of the user, such as blood glucose levels.

The coating may be applied using any suitable technique, such as sputtering, electroplating, dip coating, spray coating, spin coating, adhesion, and combinations thereof.

It will be appreciated by those skilled in the art that the coating of the electrode may be of any suitable thickness to provide sufficient conductive contact. In certain embodiments, the coating has a thickness of about 10nm to 500 microns, about 100nm to 500 microns, about 300nm to 500 microns, about 10 to 500 microns, about 50 to 500 microns, about 100 to 500 microns, about 200 to 500 microns. In certain embodiments, the coating has a thickness of less than about 500 microns, 400 microns, 300 microns, 200 microns, or 100 microns. In some embodiments, the coating has a thickness of about 0.5mm to about 5mm, about 0.5mm to about 3mm, about 0.5mm to about 2mm, preferably about 1 mm.

One skilled in the art will appreciate that the electrodes may be any suitable size depending on the size of the non-invasive device. The size of each electrode depends on at least two factors: (i) from a physical point of view, the electrode skin contact area should be as large as possible to obtain a higher quality impedance signal; (ii) from a device and comfort point of view, the electrodes should be as small as possible.

In some embodiments, the surface area of the electrode is about 2 to 100mm²About 5 to 80mm²About 2 to 60mm²About 2 to 50mm²About 2 to 40mm²About 5 to 40mm²About 10 to 40mm²About 15 to 40mm²About 20 to 40mm²Preferably about 19mm²To 36mm²More preferably about 25mm². In a preferred embodiment, each electrode has substantially about the same surface area. In certain embodiments, the surface area of the electrode is greater than about 15mm²Greater than about 20mm²Preferably greater than about 25mm²Greater than about 50mm²And greater than about 64mm²。

These surface areas of the electrodes should be selected such that they are large enough to generate a signal, but small enough to provide adequate spacing for a range of non-invasive device sizes. IEC 60601 provides international technical standards for safety and performance of medical and electrical equipment and limits both direct current and alternating current with frequencies below 1kHz to 10 mua and alternating current above 1kHz according to equation 1. The standard specifies limits for patient leakage current and patient assist current under normal conditions and single fault conditions. These current limits are important parameters in the design of electrical medical device circuits.

Equation 1. maximum alternating current at frequencies above 1 kHz.

WhereinIs the maximum alternating current, 10 μ A_RMSIs 10 μ A (root mean square value), F_EIs the excitation frequency.

For the comfort of the subject when using the non-invasive device, in certain embodiments, the electrodes should be free of surface or texture inconsistencies that can be tactilely felt on the surface by a finger. This may prevent or reduce skin irritation that may occur during use.

Those skilled in the art will appreciate that the housing may take any geometry or size, depending on the size of the electrodes and the final configuration of the non-invasive device. The housing may take any suitable shape and may be, for example, cubic, cylindrical, prismatic, tetrahedral or irregular in shape. In a preferred embodiment, the housing is adapted to minimize electrical interference to improve signal quality, such as physical and/or electrical isolation. For example, the housing may be adapted such that the electrical leads are located away from the electrodes when the device is physically connected to the receiver.

In some embodiments, the housing is made of a material selected from the group consisting of: ceramic, stone, leather, silicone rubber, copper, aluminum, platinum, titanium, gold, silver, iron, steel, stainless steel, brass, bronze, nickel, wood, bone, polymers, and combinations thereof. In certain embodiments, the polymer is selected from the group consisting of: polyvinyl chloride (PVC), High Density Polyethylene (HDPE), High Impact Polystyrene (HIPS), Polyurethane (PU), Acrylonitrile Butadiene Styrene (ABS), Polyhydroxyalkanoate (PHA), Polyhydroxybutyrate (PHB), polyvinyl alcohol-polycaprolactone (PVOH-PCL), polyglycolic acid (PGA), Polycaprolactone (PCL), polylactic acid (PLA), Polyethylene (PE), Polystyrene (PS), polypropylene (PP), and combinations thereof.

One skilled in the art will appreciate that any suitable ceramic may be used. Suitable ceramics may be selected from the group consisting of: inorganic or non-metallic (such as oxide, nitride or carbide) materials. Suitable ceramic materials may be selected from the group consisting of: ceramics (such as porcelain and clay), barium titanate, bismuth strontium calcium copper oxide, boron nitride, ferrite, lead zirconate titanate, magnesium diboride, silicon aluminum oxynitride, silicon carbide, silicon nitride, talc, titanium carbide, yttrium barium copper oxide, zinc oxide, zirconium dioxide, partially stabilized zirconium oxide, calcium sulfate, hydroxyapatite, titanium nitride, yttrium barium copper oxide, titanium nitride, yttrium barium copper oxide, zirconium dioxide, partially stabilized zirconium oxide, calcium sulfate, calcium phosphate, calcium oxide,Calcium silicate, And combinations thereof. One skilled in the art will appreciate that any suitable stone may be used. In certain embodiments, the stone is a gemstone or the like for jewelry. In certain embodiments, the stone is selected from the group consisting of: amber, amethyst, emerald, jade, jasper, onyx, diamond, quartz, ruby, sapphire, turquoise, cubic oxygenZirconium oxide and combinations thereof.

It will be appreciated by those skilled in the art that any suitable wood may be used. In certain embodiments, the wood is hardwood or softwood. In some embodiments, the wood is heartwood or sapwood. In some embodiments, the wood is selected from the group consisting of: bamboo, forest, pine, teak, spruce, larch, juniper, poplar, horntree, birch, alder, beech, oak, elm, cherry, pear, maple, basswood, ash, cedar, fir, mahogany, walnut, and combinations thereof.

One skilled in the art will appreciate that any suitable bone may be used. Typically the bone is a bone used for decorative purposes. In certain embodiments, the bone may be obtained from cattle, sheep, fish, whale, seal, dolphin, bird, deer, cattle, moose, kangaroo, crocodile, rabbit, guinea pig, and combinations thereof.

In embodiments where the shell is made of a polymer, the shell may further comprise an additive. The addition of additives to the shell can be used to adjust the physical and chemical properties of the resulting material formed thereby.

In one embodiment, the additive may be selected from the group consisting of: antioxidants, heat stabilizers, plasticizers, fillers, surfactants, lubricants, pigments, tackifiers, stabilizers, and combinations thereof.

The antioxidant can be any suitable compound to prevent or minimize oxidative degradation reactions of the shell, including phenols and phosphites. In one embodiment, the antioxidant is selected from the group consisting of: pentaerythritol tetrakis (pentaerythritols tetrakis), octadecyl-3- (3, 5-di-tert-butyl-4-hydroxyphenyl) -propionate, phenylpropionic acid, 3, 5-bis (1, 1-dimethyl-ethyl) -4-hydroxy-C7-C9 branched alkyl ester, 3',3',3',5,5',5' -hexa-tert-butyl-a, a ', a ' - (mesitylene-2, 4, 6-triyl) tri-p-cresol, tris- (3, 5-di-tert-butyl-4-hydroxybenzyl) isocyanurate, 2', 3-bis [3- (3, 5-di-tert-butyl-4-hydroxyphenyl) propionyl ] -propionohydrazide, N ' -hexane-1, 6-diylbis (3- (3, 5-di-tert-butyl-4-hydroxyphenyl-propionamide)), 4, 6-bis (dodecylthiomethyl) -o-cresol, 4, 6-bis (octylthiomethyl) -o-cresol, 2' -methylenebis (4-methyl-6-tert-butylphenol), 2, 6-di-tert-butyl-4- [ [4, 6-bis (octylthio) -1,3, 5-triazin-2-yl ] amino ] phenol, tris (2, 4-di-tert-butylphenyl) -phosphite, bis (2, 4-di-tert-butylphenyl) -pentaerythritol diphosphite, and combinations thereof.

The heat stabilizer may be any suitable compound to improve the resistance of the shell to discoloration. The heat stabilizer may be a lead compound, an organotin compound, other metal compound and an organic stabilizer. In one embodiment, the heat stabilizer is selected from the group consisting of: lead sulfite, lead carbonate, lead stearate, dibutyltin maleate, barium cadmium stearate, barium cadmium zinc stearate, methyl tin mercaptide, methyl tin ester, butyl tin thioglycolate, n-octyl tin mercaptide, butyl tin carboxylate, 3- (2, 4-dichlorophenyl azo) -9- (2, 3-propylene oxide) carbazole, barbituric acid, thiobarbituric acid, poly (hexanediol adipate), poly (ethylene adipate), poly (hexanediol terephthalate), and poly (ethylene terephthalate), and combinations thereof.

Plasticizers can be added to the shell to improve processing characteristics while also providing flexibility to the end use product. The plasticizer may be selected from the group consisting of: ester plasticizers, sebacates, adipates, terephthalates, dibenzoates, glutarates, phthalates, azelates, and combinations thereof.

The filler may be any suitable compound to reduce the amount of polymer required in the shell. In one embodiment, the filler is selected from the group consisting of: aluminum silicate, potassium silicate, calcium silicate, silicon dioxide, sodium silicate, clay, kaolin, alumina, limestone, barium sulfate, strontium sulfate/selenite, magnesium oxide, calcium carbonate, dolomite, metal powders or flakes, ceramic beads, magnesium silicate, and combinations thereof.

The surfactant may be any suitable compound to provide a surface active film. In one embodiment, the surfactant is anionic, cationic, zwitterionic, or nonionic. In one embodiment, the surfactant comprises a functional group selected from the group consisting of: sulfates, sulfonates, phosphates, carboxylates, amines, ammonium, alcohols, ethers, and combinations thereof. In one embodiment, the surfactant is selected from the group consisting of: sodium stearate, 4- (5-dodecyl) benzenesulfonate, 3- [ (3-cholamidopropyl) dimethylammonio ] -1-propanesulfonate, phosphatidylserine, phosphatidylethanolamine, phosphatidylcholine, octaethyleneglycol monododecyl ether, pentaethyleneglycol monododecyl ether, decyl glucoside, lauryl glucoside, octyl glucoside, triton X-100, nonoxynol-9, glyceryl laurate, polysorbate, dodecyldimethylamine oxide, polysorbate, cocamide monoethanolamine, cocamide diethanolamine, poloxamers, polyethoxylated tallow amine, and combinations thereof.

The lubricant may be any suitable compound to reduce internal and/or external friction of the housing during processing. In one embodiment, the lubricant is an amide, an acid ester, a fatty acid, a hydrocarbon wax, a metal soap, or a combination thereof. In one embodiment, the lubricant is selected from the group consisting of: zinc laurate, zinc stearate, calcium laurate, calcium stearate, lead stearate, magnesium stearate, aluminum stearate, sodium stearate, tin stearate, barium stearate, cobalt stearate, paraffin wax, mineral oil, erucamide, oleamide, stearamide, ethylene bis oleamide, montan wax, stearyl stearate, distearyl phthalate, lauric acid, myristic acid, palmitic acid, stearic acid, oleic acid, erucic acid, molybdenum disulfide, mica, niobium (IV) selenide, bromine, or metal chloride intercalated graphite, and combinations thereof.

The pigment may be any suitable compound to impart color to the resulting shell. In one embodiment, the pigment is an inorganic pigment or an organic pigment. In one embodiment, the pigment is derived from a compound selected from the group consisting of: acridine, anthraquinone, diarylmethane, triarylmethane, azo, diazo, nitro, nitroso, phthalocyanine, quinone, thiazine, oxadiazon (oxazone), oxazine (oxazin), indoxyl, thiazole, safranin, xanthene, fluorene, fluorone, and combinations thereof. In one embodiment, the pigment is selected from the group consisting of: cadmium yellow, cadmium red, cadmium green, cadmium orange, cadmium sulfoselenide, chrome yellow, chrome green, cobalt violet, cobalt blue, cyanine blue, cobalt yellow, chalcopyrite, han violet, han blue, egyptian blue, malachite, paris green, phthalocyanine blue BN, phthalocyanine green G, verdigris, chrome green, red blood, kappat red, red oxide, ochre red, venetian red, prussian blue, white lead, pure white lead, naparh yellow, red lead, manganese violet, vermilion, titanium yellow, titanium white, titanium black, zinc white, zinc ferrite, carbon black, ivory black, yellow ochre, raw ochre, burnt brown, ultramarine green, alizarin dark red, gamboge, rubicin, rose grass color, indigo blue, yellow violet, quinacridone, magenta, phthalocyanine green, phthalocyanine blue, pigment red 170, diarylide yellow, and combinations thereof.

The tackifier may be any suitable compound to impart adhesion to the resulting shell. In one embodiment, the tackifier is selected from the group consisting of: rosin resins, hydrocarbon resins, terpene resins, and combinations thereof. In one embodiment, the rosin resin is selected from the group consisting of: rosin esters, hydrogenated rosin resins, dimerized rosin resins, and combinations thereof. In one embodiment, the rosin resin is derived from wood rosin, gum rosin, tall oil rosin, or combinations thereof.

In one embodiment, the hydrocarbon resin is C₅Alkyl resin, C₅Alkenyl resin, C₉An aryl resin, or a combination thereof. In one embodiment, the terpene resin is a terpene phenol resin, an alkyl terpene resin, an alkenyl terpene resin, an aryl terpene resin, or a combination thereof.

The stabilizer may be any suitable compound that can directly or indirectly reduce the effect of ultraviolet radiation. In one embodiment, the stabilizer is a uv absorber, a hindered amine light stabilizer, and combinations thereof. In one embodiment, the ultraviolet absorber is a hindered phenol. In one embodiment, the stabilizer is selected from the group consisting of: 4-allyloxy-2-hydroxybenzophenone, 1-aza-3, 7-dioxabicyclo [3.3.0] octane-5-methanol, tris (nonylphenyl) phosphite, 1,3, 5-tris (2-hydroxyethyl) isocyanurate, tris (2, 4-di-tert-butylphenyl) phosphite, tris (4-tert-butyl-3-hydroxy-2, 6-dimethylbenzyl) isocyanurate, 1,3, 5-trimethyl-2, 4, 6-tris (3, 5-di-tert-butyl-4-hydroxybenzyl) -benzene, triisodecyl phosphite, tetrachloro-1, 4-benzoquinone, sodium D-isoascorbate monohydrate, poly [ [6- [ (1,1,3, 3-tetramethylbutyl) amino ] -s-triazine-2, 4-diyl ] - [ (2,2,6, 6-tetramethyl-4-piperidyl) imino ] -hexamethylene- [ (2,2,6, 6-tetramethyl-4-piperidyl) imino ], 2-phenyl-5-benzimidazolesulfonic acid, pentaerythrityl tetrakis (3, 5-di-tert-butyl-4-hydroxyhydrocinnamate), octadecyl 3- (3, 5-di-tert-butyl-4-hydroxyphenyl) propionate, 4-nitrophenol sodium salt, methylhydroquinone, 5' -methylenebis (2-hydroxy-4-methoxybenzophenone), 2' -methylenebis (6-tert-butyl-4-methylphenol), 2' -methylenebis (6-tert-butyl-4-ethylphenol), 2,2 '-methylenebis [6- (2H-benzotriazol-2-yl) -4- (1,1,3, 3-tetramethylbutyl) phenol ], methyl-p-benzoquinone, 2-methoxyhydroquinone, menthyl anthranilate, 2-hydroxy-4- (octyloxy) benzophenone, 2' -ethylene-bis (4, 6-di-tert-butylphenol), 2-ethylhexyl salicylate, trans-4-methoxycinnamic acid-2-ethylhexyl ester, 2-cyano-3, 3-diphenylacrylic acid ethyl ester, 5-ethyl-1-aza-3, 7-dioxabicyclo [3.3.0] octane, 3' -thiodipropionic acid ditridecyl ester, 2- (4, 6-diphenyl-1, 3, 5-triazin-2-yl) -5- [ (hexyl) oxy ] -phenol, 4-dimethyloxazolidine, 2, 3-dimethylhydroquinone, 2',4' -dihydroxy-3 ' -propylacetophenone, 2' -dihydroxy-4-methoxybenzophenone, 2' -dihydroxy-4, 4' -dimethoxybenzophenone, 2, 4-dihydroxybenzophenone, 3' -thiodipropionic acid ditridecyl ester, 3',5' -dichloro-2 ' -hydroxyacetophenone, 2, 6-di-tert-butyl-4- (dimethylaminomethyl) phenol, di-tert-butyl-4- (dimethylamino-methyl) phenol, di-tert-butyl-2-hydroxy-benzophenone, di-tert-butyl-3, 3' -dimethyloxa-2 ' -dimethylol, di-tert-butyl-4- (2-methyl) phenol, di-hydroxy-2, 4' -dimethylol, 2, 4' -dimethylol, and mixtures thereof, 2, 4-di-tert-butyl-6- (5-chloro-2H-benzotriazol-2-yl) phenol, 5-chloro-2-hydroxy-4-methylbenzophenone, 5-chloro-2-hydroxybenzophenone, 2-tert-butyl-4-ethylphenol, 2-tert-butyl-6- (5-chloro-2H-benzotriazol-2-yl) -4-methylphenol, bis (2,2,6, 6-tetramethyl-4-piperidinyl) sebacate, bis (1-octyloxy-2, 2,6, 6-tetramethyl-4-piperidinyl) sebacate, 3, 9-bis (octadecyloxy) -2,4,8, 10-Tetraoxa-3, 9-diphosphaspiro [5.5] undecane, bis (octadecyl) -hydroxylamine, 3, 9-bis (2, 4-dicumylphenoxy) -2,4,8, 10-tetraoxa-3, 9-diphosphaspiro [5.5] undecane, ethyl 2- (4-benzoyl-3-hydroxyphenoxy) acrylate, 2- (2H-benzotriazol-2-yl) -4- (1,1,3, 3-tetramethylbutyl) phenol, 2- (2H-benzotriazol-2-yl) -4-methyl-6- (2-propenyl) phenol, 2- [3- (2H-benzotriazol-2-yl) -4-hydroxyphenyl ] -ethyl methacrylate, 2- (2H-benzotriazol-2-yl) -6-dodecyl-4-methylphenol, 2- (2H-benzotriazol-2-yl) -4, 6-di-tert-amylphenol, 2- (2H-benzotriazol-2-yl) -4, 6-bis (1-methyl-1-phenylethyl) phenol, and combinations thereof.

It should be appreciated that the additives discussed above may be added to the housing in any suitable amount to provide the desired characteristics. In one embodiment, the additive is added to the housing in an amount of about 0.01 to about 50 wt%, in an amount of about 1 to about 50 wt%, in an amount of about 10 to about 40 wt%, in an amount of about 10 to about 30 wt%, or in an amount of about 20 to about 30 wt%.

The housing may be manufactured using any suitable technique. For example, the housing may be made by injection molding, engraving, extrusion, blowing, rotational molding, thermoforming, calendering, stamping, CNC machining, embossing, 3D printing, casting, and extrusion.

In certain embodiments where both the electrode and the housing are conductive materials, the non-invasive device comprises an insulator disposed between the electrode and the housing to prevent or mitigate the risk of short circuits or electrical interference.

As will be appreciated by those skilled in the art, preferably, the electrodes of the non-invasive device should be substantially in contact with the subject's skin surface at a constant pressure during use to minimize artifacts and poor data measurement. In certain embodiments, the non-invasive apparatus includes an adjustable electrode contact mechanism to ensure measurement of high quality impedance signals while maintaining comfort to the subject. In this embodiment, the contact area of the electrodes may be automatically adjusted to ensure sufficient contact between the electrodes and the subject's skin to receive a high quality impedance signal. For example, the adjustable electrode contact mechanism may be a screw and/or spring fastener. This may ensure that the electrodes protrude from the housing to improve contact between the electrodes and the subject's skin to receive high quality impedance signals. In other embodiments, a device such as a finger ring may be made of a resilient material and optionally include a notch or webbing to accommodate different sizes of a portion of the body (e.g., a finger). For example, in some embodiments, a device such as a finger ring may accommodate expansion at the knuckle and then contraction at the base of the finger to ensure adequate contact.

In certain embodiments, the function of the electrodes may be adjusted using a Printed Circuit Board (PCB) connected to the non-invasive device without physical modification, such that the electrodes may be controlled by the PCB to function as stimulation electrodes, sensing electrodes, or sink terminals. In these embodiments, the immediate adjustment of the function of the electrodes by the PCB may ensure the measurement of a high quality impedance signal.

It will be appreciated by those skilled in the art that the non-invasive device may be in any suitable form, such as a wearable device. In some embodiments, the non-invasive device may be a smart watch, a belt, a band (e.g., a waist band or an arm band), a bracelet, a ring, a clip (e.g., for ears or fingers), or a desktop device. For example, if the non-invasive device is in the form of a waist band, the electrodes may be provided as a patch that is inserted into the waist band for use with the subject. If the non-invasive device is a smart watch or ring, the electrodes may be mounted in a housing so that the device can be connected to a mobile electronic device (e.g., mobile phone/phone, tablet, laptop, personal computer, etc.).

In certain embodiments, the non-invasive apparatus includes a notification indicator. The notification indicator may be in the form of a light (e.g., an LED), a screen, a visual alarm, a tactile alarm, an audible alarm, and combinations thereof. The indicator may display, for example, the operational status of the non-invasive device, such as whether the device is powered on/off, in a normal operational state, in an error state, etc. In some embodiments, the notification indicator may alert the subject or remote user if the blood glucose concentration is outside a predetermined range, such as above or below a normal threshold range. In some embodiments where the indicator is a screen, the indicator may provide information such as duration of operation, real-time blood glucose concentration, impedance signal strength and quality, connection status, and the like.

In some embodiments, the receiver is an Electrochemical Impedance Spectroscopy (EIS) device, a microprocessor, or a microcontroller to receive the impedance signal from the electrodes of the non-invasive device. In certain embodiments, the non-invasive apparatus comprises a receiver (i.e., the receiver is integral with the apparatus). In certain embodiments, the receiver is external to the non-invasive device. In these embodiments, the receiver may be connected to the non-invasive device using a wired connection or a wireless connection to transmit the impedance data.

In certain embodiments, the non-invasive apparatus includes a faraday shield to reduce interference and improve impedance signal quality.

In some embodiments, the non-invasive device comprises a probe for measuring an additional physiological parameter (i.e., biometric information) of the subject. For example, the probe may be used to measure body fat, muscle mass, body composition, body temperature, skin pH, skin temperature, blood pressure, heart rate, and the like. In these embodiments, the probe may be an electrode, thermocouple, or spectrophotometer. For example, if heart rate is measured, an LED source may be provided and an LED sensor may be used to measure the light signal and then an algorithm is used to compare the difference in the signals to output the subject's heart rate.

In some embodiments, the non-invasive device may be integrally formed with, attached to, or at least partially surrounding (surround) or enclosing (encompass) the third party device. Any suitable third party device may be used which may contact the skin of the subject so that the impedance signal may be measured. For example, the third party device may be a cell phone; a handset housing; computer peripherals such as a keyboard or mouse; furniture such as chairs, sofas or couches; audio devices, such as headphones; glasses; a garment; footwear; a container, such as a beverage or food container.

In certain embodiments, the non-invasive device comprises a communication device. The communication device may be a communication transmitter or a communication receiver for transmitting or receiving data. In these embodiments, the communication device may transmit or receive data over a wireless or cellular network. Advantageously, the communication device may transmit the raw impedance data to a remote or cloud-based computer, such as a supercomputer, base station, server, or other device, such as a smartphone, laptop, or tablet computer, to remotely calculate and determine the blood glucose concentration. In this embodiment, the blood glucose concentration of a subject, such as a child, elderly, or at-risk individual, may be monitored even without the use of a computer or cell phone. This may be used to provide an alert to a remote user that the subject has exceeded a predetermined blood glucose concentration threshold. In other embodiments, the computing may be processed by a non-invasive device and the data may be transmitted to a remote or cloud-based computer.

In use, the non-invasive device is worn such that the electrodes are in conductive skin contact with the subject. For example, the skin site may be located on the volar side of the forearm, below the wrist, behind the ear, above the ear, on the earlobe, or on the finger of the subject. In some cases, the skin may be pre-treated prior to the measuring step or prior to wearing, such as with a physiological saline or alcohol solution (e.g., an isopropyl alcohol solution) or shaving. A conductive gel may be selectively applied to the skin to enhance the conductive contact of the electrodes with the skin surface during the measuring step.

The electrodes may be operatively connected to a microprocessor programmed to determine the amount of blood glucose based on the measured impedance. There may be an indicator operably connected to the microprocessor for indicating the determined amount of blood glucose to the subject. The indicator may provide a visual display to the subject.

In certain embodiments, the microprocessor may be operably connected to an insulin pump and programmed to regulate the flow of insulin to the subject via the pump in response to the measured blood glucose amount.

The microprocessor may be programmed to compare the measured impedance to a predetermined correlation between impedance and blood glucose concentration. The non-invasive device may include a receiver to measure impedance at multiple frequencies.

In operation, the non-invasive device may calibrate the device for a directly measured glucose concentration of the subject. The device may input a directly measured glucose concentration value and an approximately simultaneously measured impedance for use by the operating software to later determine the subject's blood glucose level based solely on subsequent impedance measurements.

In some embodiments, data generated by a non-invasive device may be collected, stored (e.g., remotely), and compiled for analysis.

According to another aspect, the present invention provides a method for non-invasive determination of blood glucose concentration in a subject, said method comprising the steps of: measuring impedance through a portion of the subject using at least two electrodes in conductive contact with the subject's skin; and determining the blood glucose level of the subject based on the measured impedance, wherein the at least two electrodes are in a configuration that passes current through the portion of the subject.

According to another aspect, the present invention provides a method for non-invasively determining the blood glucose concentration of a subject, the method comprising the steps of: measuring impedance through a portion of the subject using at least two electrodes in conductive contact with the subject's skin; determining the subject's blood glucose based on the measured impedance; and measuring at least one additional physiological parameter of the subject.

One skilled in the art will appreciate that any suitable frequency may be used to measure impedance. In some embodiments, the impedance is measured at a plurality of frequencies. In some embodiments, the amount of blood glucose concentration is determined by determining an impedance ratio at a plurality of frequencies, such as a ratio of two frequencies. In certain embodiments, the method is performed at a frequency range of about 0.1Hz to about 1MHz, about 5Hz to about 1MHz, about 20Hz to about 1MHz, about 5Hz to about 800kHz, about 5Hz to about 500kHz, about 2Hz to about 500 kHz.

In some embodiments, the methods of the invention are performed using Alternating Current (AC). In some embodiments, the methods of the invention are performed using Direct Current (DC).

In some embodiments, the portion of the subject is a body portion of the subject. In some embodiments, the portion of the subject is selected from the group consisting of: fingers, ears, waist, legs, arms, wrists, and combinations thereof.

In certain embodiments, the process of the invention is continuous. In some embodiments, the methods of the invention are measured at intervals. In some embodiments, the duration of each single measurement of blood glucose concentration is from about 2 seconds to about 10 minutes, from about 2 seconds to about 5 minutes, from about 2 seconds to about 3 minutes, from about 2 seconds to about 2 minutes. In some embodiments, the duration of each single measurement of blood glucose concentration is less than about 10 minutes, less than about 5 minutes, less than about 3 minutes, less than about 90 seconds, less than about 60 minutes, less than about 30 seconds. In some embodiments, the duration of each single measurement of blood glucose concentration is less than 48 hours, less than 30 hours, less than 24 hours, less than 12 hours, less than 8 hours, less than 4 hours, less than 2 hours, less than 1 hour.

In some embodiments, the methods of the invention measure impedance at intervals of about 2 seconds to 60 minutes, about 2 seconds to 30 minutes, about 2 seconds to 10 minutes, about 2 seconds to 5 minutes, about 2 seconds to 3 minutes, about 2 seconds to 1 minute, about 2 seconds to 30 seconds, about 2 seconds to 15 seconds, about 2 seconds to 10 seconds, about 2 seconds to 5 seconds. In some embodiments, the methods of the present invention measure impedance at about 2 seconds, about 5 seconds, about 10 seconds, about 15 seconds, about 30 seconds, about 1 minute, about 3 minutes, about 5 minutes, about 10 minutes. In some embodiments, the method of the invention measures impedance continuously or repeatedly to provide a substantially continuous measurement at intervals.

In certain embodiments, the methods of the invention further comprise measuring at least one additional physiological parameter in the subject. In certain embodiments, the physiological parameter (i.e., biometric information) is selected from the group consisting of: body fat, muscle mass, body composition, body temperature, skin pH, skin temperature, blood pressure, heart rate, and combinations thereof.

In some embodiments, the method comprises a pretreatment step, wherein the pretreatment step involves shaving and/or cleansing the skin. The skin can be cleansed with a physiological saline or alcohol solution (e.g., an isopropyl alcohol solution) prior to the measuring step or prior to wearing. In some embodiments, a conductive layer (e.g., in the form of a gel, paste, ointment, or cream) may be applied to the skin to enhance the conductive contact of the electrodes with the skin surface during the measuring step.

In certain embodiments, the methods of the invention comprise the use of artificial neural networks. In certain embodiments, the methods of the present invention include using an Artificial Neural Network (ANN) to process the impedance signal to improve signal quality. In certain embodiments, the methods of the invention comprise performing a non-linear regression using an artificial neural network. In certain embodiments, the methods of the invention comprise using an artificial neural network to predict and/or determine the blood glucose concentration of a subject. In certain embodiments, an Artificial Neural Network (ANN) model correlates measured biometric information (including but not limited to bio-impedance, body temperature, skin pH, blood pressure, etc.) to blood glucose concentration. In some embodiments, different ANN architectures or models may be used depending on the form factor of the non-invasive device (e.g., whether the device is a ring, bracelet, smart watch, or other form). In certain embodiments, the methods of the present invention comprise dynamically adaptive ANN. In this embodiment, the dynamically adaptive ANN enables the non-invasive device to adapt to a particular physiological parameter pattern of the subject, which increases the accuracy of blood glucose concentration measurements by the subject when in use and worn.

As previously discussed, the present invention provides a non-invasive device that can measure impedance with high quality signals. This allows the user (who may also be a subject) to monitor the quality of the output current signal before using the data to determine blood glucose concentration. This allows for improved accuracy or enabling the function of the ANN in determining blood glucose concentration by removing noise and low quality signals and using only the high quality data of the ANN to select the quality data.

According to another aspect, the present invention provides a kit comprising: at least two electrodes adapted to be connected to a receiver to measure an impedance signal; and a housing adapted to receive the electrode.

In some embodiments, the kit comprises a receptacle. In some embodiments, the receiver is an Electrochemical Impedance Spectroscopy (EIS) device. In some embodiments, the kit comprises an insulin pump.

Definition of

In describing and claiming the present invention, the following terminology will be used in accordance with the definitions set out below. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments of the invention only and is not intended to be limiting. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Throughout the specification and claims, the words "comprise," "comprising," and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense, unless the context clearly requires otherwise; that is, in the sense of "including, but not limited to".

As used herein, the phrase "consisting of … …" excludes any element, step, or ingredient not specified in the claims. When the phrase "consisting of … …" (or variants thereof) appears in a later part of the claim body, rather than immediately following the former part, it limits only the elements recited in that later part; no other elements are excluded from the claims as a whole. As used herein, the phrase "consisting essentially of … …" limits the scope of the claims to the specified elements or method steps, as well as those elements or method steps that do not materially affect the basic and novel characteristics of the claimed subject matter.

With respect to the terms "comprising," "consisting of … …," and "consisting essentially of … …," where one of these three terms is used herein, the presently disclosed and claimed subject matter can include the use of either of the other two terms. Thus, in some embodiments not explicitly recited otherwise, any instance of "comprising" may be replaced by "consisting of … … or alternatively" consisting essentially of … … ".

Other than in the operating examples, or where otherwise indicated, all numbers expressing quantities of ingredients or reaction conditions used herein are to be understood as being modified in all instances by the term "about" in view of the normal tolerances in the art. The examples are not intended to limit the scope of the invention. Hereinafter, or in the case of other explanations, "%" will mean "% by weight", "ratio" will mean "weight ratio", and "part" will mean "part by weight".

The term "substantially" as used herein, unless otherwise specified, means containing more than 50% by weight where relevant.

The recitation of numerical ranges by endpoints includes all numbers subsumed within that range (e.g. 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, 5, etc.).

The terms "preferred" and "preferably" refer to embodiments of the invention that may provide certain benefits under certain conditions. However, other embodiments may be preferred, under the same or other circumstances. Furthermore, the recitation of one or more preferred embodiments does not imply that other embodiments are not useful, and is not intended to exclude other embodiments from the scope of the invention.

It must also be noted that, as used in the specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise.

The prior art cited herein is fully incorporated by reference.

Although exemplary embodiments of the disclosed technology are explained in detail herein, it is to be understood that other embodiments are contemplated. Therefore, it is not intended that the scope of the disclosed technology be limited to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The disclosed technology is capable of other embodiments and of being practiced or of being carried out in various ways.

Drawings

Preferred embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

figure 1 shows a setup for measuring the impedance of the arm of a human hand using imprimed gel electrodes for Keysight E4990A.

Figure 2 shows the results of 4T (four electrode) arm measurements using the inphase system compared to imprimed SFB 7.

Fig. 3 shows an embodiment of a non-invasive device in the form of a wearable finger ring having eight holes adapted to accommodate up to 8 electrodes.

Fig. 4 shows a gold plated copper electrode.

Fig. 5 shows an embodiment of a non-invasive device in the form of a wearable finger ring with eight electrodes.

Fig. 6 shows different housing configurations of a non-invasive device for 3D printing.

Figure 7 shows a 4T (four electrode) non-invasive device in the form of a wearable finger ring with an alternative configuration.

Figure 8 shows 4T finger ring measurements with 7 repetitions of the embodiment of figure 7. a) Average impedance versus frequency, b) average phase versus frequency, c) average conductance versus frequency, and d) average capacitance versus frequency.

Figure 9 shows the measured signal quality for the finger ring embodiment of figure 7.

Figure 10 shows a fully assembled non-invasive device in the form of a bracelet.

Fig. 11 shows 4T bracelet measurements (4 replicates) using the EIS of the embodiment of fig. 10. a) Average impedance versus frequency, and b) average phase versus frequency.

Fig. 12 shows 4T bracelet measurements (4 replicates) using the inphase system of the embodiment of fig. 10 (4 replicates). a) Average impedance versus frequency, and b) average phase versus frequency.

Figure 13 shows the measured signal quality of the bracelet embodiment of figure 10.

Figure 14 shows a 4-terminal (4T) configuration of a non-invasive device in the form of a wearable finger ring for use in a human trial.

Figure 15 shows the measured signal quality of the 4T ring of the embodiment of figure 14.

Figure 16 shows 4T impedance wrist measurements using imprimed SFB7 and imprimed gel electrodes.

Fig. 17 shows electrical interference with a bioimpedance signal.

Figure 18 shows an embodiment of a faraday cage for bio-impedance measurements.

Fig. 19 shows the effect on the impedance signal before and after the introduction of electrical interference on the resistor, showing no interference.

Figure 20 shows a) measurements of the ring impedance outside the faraday cage with electrical interference nearby, and b) measurements of the ring impedance inside the faraday cage with electrical interference placed directly on the top and sides of the faraday cage.

Figure 21 shows the results of the first clinical Oral Glucose Tolerance Test (OGTT) performed on participant 1, comparing clinical blood glucose concentrations with those measured using Accu-Chek and Freestyle Libre devices.

Figure 22 shows the results of a second clinical Oral Glucose Tolerance Test (OGTT) performed on participant 1, comparing clinical blood glucose concentrations with those measured using Accu-Chek and Freestyle Libre devices.

Figure 23 shows the results of a clinical Oral Glucose Tolerance Test (OGTT) performed on participant 2, comparing clinical blood glucose concentrations with those measured using an Accu-Chek device.

FIG. 24 shows Clark (Clarke) error grid (CEG).

FIG. 25 shows the parkers (Parkes) error grid (PEG) for type 1 (A) and type 2 (B) diabetes.

Fig. 26 shows a monitoring (surveyability) error grid (SEG).

Figure 27 shows an example of a document of BGL range from different participant groups.

FIG. 28 shows a PEG map (type 1 diabetes) showing early Accu-Chek and Freestyle library data collected from participants 1 and 2. The range in the x-axis and y-axis has been adjusted for better visualization.

Figure 29 shows early bioimpedance results through the whole body using the imprimed device. Measurements taken at 3 different time points are shown, with 5 measurements taken at each time point.

Fig. 30 shows an imprimed gel electrode configuration for measuring bio-impedance through a) the upper forearm, b) the lower forearm and c) through the finger.

Fig. 31 shows a typical kola (Cole) plot of bioimpedance measurements by (a) whole body, (B) forearm (upper and lower side) and (C) finger using an imprimed device.

Fig. 32 shows electrode placement positions on (a, b) participant 1 and (c, d) participant 2 for whole body bioimpedance measurements using an imprimed device.

Fig. 33 shows a graph comparing each blood glucose concentration (BGL) measurement value (Accu-Chek) at 51.172Hz of (a) participant 1 and (B) participant 2 with bioimpedance values (imprimed). All 5 measurements made during a single bio-impedance measurement are shown. In case of multiple measurements at the same BGL value, different colors/symbols (BGL #1- #5) are used to distinguish between these.

Fig. 34 shows an example of a Parks Error Grid (PEG) diagram.

Fig. 35 shows a) EIS instrument, b) prototype dry electrodes in a ring-shaped housing for c) bio-impedance measurements by finger.

Fig. 36 shows the electrode placement positions on participant 1 for bioimpedance measurements (a, b) through the whole body or (c, d) through the wrist.

Fig. 37 shows the electrode placement positions on participant 2 for bioimpedance measurements (a, b) through the whole body or (c, d) through the wrist.

Fig. 38 shows the electrode placement positions on participant 3 for bioimpedance measurements (a, b) through the whole body or (c, d) through the wrist.

Figure 39 shows the ring and electrode placement position on participant 2 for bio-impedance measurements by finger.

Figure 40 shows photographs of each stage of a human test. The following measurements are shown: BGL generated by (g, i) Accu-Chek and (h) Freestyle Libre, (j) blood pressure and heart rate, and (k, l) skin pH of the whole body, (m) wrist, and (n) finger by (a) bio-impedance of the whole body, (d) wrist, and (e) finger, (b) skin temperature of the whole body, (c) wrist, and (f) finger.

Fig. 41 shows a photograph illustrating proper lead placement for bioimpedance measurements.

FIG. 42 shows a decision making facilityPreparing a flow chart of a clinical test. BGL represents blood glucose concentration/level and BI represents bio-impedance.¹At least one component of the test stand was not TGA approved. For example, a non-medical EIS machine with a prototype electrode, a TGA-approved EIS machine with a prototype electrode, or any other combination is used.²The product is ready for sale, except at this stage, TGA approval has not been obtained.

Fig. 43 shows (a) a top view and (b) a bottom view of an alternative electrode configuration of an embodiment of a non-invasive device in the form of a ring.

Fig. 44 shows (a)8 differently configured electrodes for an embodiment of a non-invasive device in the form of a ring, with arrows showing current paths for the 8 configurations and (b) bioimpedance data.

Fig. 45(a) and (b) show an alternative configuration of an embodiment of the non-invasive device in the form of a ring or wearable device.

Figure 46 shows representative bio-impedance results for square and circular electrodes of an embodiment of a non-invasive device in the form of a finger ring.

Fig. 47 shows representative bio-impedance results using different sized electrodes of an embodiment of the non-invasive device in the form of a finger ring.

Fig. 48 shows the effect of electrode spacing on bio-impedance measurements of an embodiment of a non-invasive device in the form of a finger ring.

Detailed Description

One skilled in the art will appreciate that the present invention encompasses the embodiments and features disclosed herein as well as all combinations and/or permutations of the disclosed embodiments and features.

Example 1 Electrical Impedance Spectroscopy (EIS) Instrument validation and selection

For impedance measurements of a subject (preferably, a human subject), a non-invasive device will be worn and the device will collect bioimpedance data over a compact period of time.

One embodiment of the apparatus consists of 2 main parts: a front end, where the test participants will "wear" the electrodes to make electrical contact with the skin; at the back end, where the EIS instrument will collect bioimpedance data for the subject via the electrodes. The main design considerations include:

front-end: placing an electrode; a method of fixing the electrode; electrode contact area; wet or dry contact with the skin; the materials to be used; and

back-end: resolution of the EIS instrument; a measured test frequency range; the range of impedances observed; reliability of bio-impedance measurements in complex motion systems, such as the human body.

To determine whether the use of non-invasive bioimpedance measurements by skin contact would provide distinguishable readings for different blood glucose concentrations, the present inventors needed an EIS instrument with good accuracy, a wide measurement frequency range, and a wide measurable impedance range. As regards the measurement frequency, there is no precise study in the literature showing which information can be obtained at lower frequencies. Thus, for the selection criteria, low frequencies are measured and can be processed later to determine their usefulness. For measurements below 1Hz, a long duration is required to capture the data, which may not be practical for non-invasive devices. At higher frequencies, intracellular and extracellular electrolytes in vivo can act as short circuits when used for impedance measurements, and therefore the required measurement frequency should not exceed kHz, preferably in the 1MHz range.

Table 1 summarizes some common EIS instruments on the market today.

Table 1: commercially available enclosed EIS instruments are contemplated for this project.

Standard EIS instruments are: solartron 1260A, Keysight E4990A-010, Newton4th PSM1735+ IAI and BioLogic MTZ-35.

Keysight E4990A was chosen as the main common EIS instrument for non-invasive devices, considering cost, performance and lead time. For additional bioimpedance measurements specifically intended to provide body composition readings, such as fat mass removal (FFM), Fat Mass (FM), Total Body Water (TBW), intracellular fluid (ICF), extracellular fluid (ECF), impedimetd SFB7 was used. ImpediMed SFB7 may also be used to make general EIS measurements, but the frequency range is limited to 4KHz to 1MHz and the measurable impedance range is below 1.1 KW.

The test protocol for the Keysight E4990A-010 general EIS instrument is as follows:

1. high precision resistors were measured and their performance determined.

And (3) performance verification: the proximity of the measured impedance Z to the resistance value is determined, as well as the proximity of the measured phase to zero, where zero is the theoretical phase value of a pure resistance independent of frequency.

2. The known Max-wagner (mw) circuit was measured as a sample and its performance was determined. The Max-Wagner circuit is composed of a plurality of R// C (resistor// capacitor) elements connected in series.

And (3) performance verification: the proximity of the reconstruction circuit (using measured EIS data) to the known circuit is determined.

3. The impedance of the human arm was measured in a 4-terminal configuration using gel electrodes from imprimed (imprimed 292-STE).

And (3) performance verification: the results were compared to measurements of the same arm obtained using imprimed SFB 7.

Performance of EIS instruments

Keysight E4990A

Test circuit

Keysight E4990A attached calibration certificates and 100 Ω test boxes. The test cartridge was first used to familiarize the system and determine its performance.

Significant Z and phase errors were observed when using a1 meter long cable measurement resistor or MW circuit. System performance was improved after phase and load compensation as described in the configuration section by the four-terminal pair according to the manufacturer's impedance measurement manual (Keysight Technologies 2016). With more test runs on known samples such as resistors and MW circuits, the Keysight E4990A instrument was validated and considered to work well as a general EIS system, which provides a measurement frequency range of 20Hz to 1 MHz.

Gel electrode

The impedance of the human arm was then measured with an imprimed gel electrode using a Keysight E4990A instrument. The Keysight E4990A instrument was considered to be at very low risk when producing zero DC bias and AC amplitudes of up to 1V. Imprimed gel electrodes were used because they have been approved by the FDA (united states food and drug administration) and TGA (australian therapeutic supplies authority) and the results can be compared to those obtained using the imprimed SFB7 instrument. The setup is as shown in figure 1.

ImpediMed SFB7

Test circuit

Since the measurable impedance range of the imprimed SFB7 instrument is limited (up to 1K Ω), a 100 Ω resistor was measured for verification, rather than the Max-Wagner circuit. In this application the imprimed SFB7 is used primarily for its intended purpose, providing body composition measurements.

Inphaze high resolution EIS

Test circuit

The Inphaze EIS instrument is a general-purpose EIS system. It is designed specifically for high resolution measurements and therefore the measurement time is very long. A typical 1Hz to 1MHz scan (3 spectra) takes about 10 minutes. Due to its useful ability to explore samples with unknown impedance, it was used to evaluate various electrode designs of the non-invasive apparatus of the present invention. The Inphaze system is also used to cross-validate results from other EIS devices, with comparability.

The Inphaze impedance analyzer software was used to automatically reconstruct the Max-Wagner circuit and plot impedance, phase and Nyquist curves. A converter utility was developed to convert data files generated by Keysight E4990A and imprimed SFB7 into a ". izx" file format compatible with the inphase impedance analyzer software.

Gel electrode

Measurements on human subjects using the inphase system are considered to be at very low risk when the dc bias is zero and the ac amplitude is at most 1V. Figure 2 shows 4T (four electrode) human arm measurements obtained with the inphase instrument and imprimedmdsfb 7. Good overlap is generally observed, but imprimed SFB7 produces a large phase error at higher frequencies, which can be confirmed by its 100 Ω resistor verify run (2 degree error). Furthermore, the phase distribution (profile) shape of the inphase measurement (as shown in fig. 2) appears to be closer to the shape one would expect in such a multilayer (electrical equivalent) sample.

EIS instrument

The inventors have also used EIS systems that work on the same principle as the inphase system.

Test circuit

The performance of the EIS solution is very similar to the inphase high resolution system. The measurement time for the scan from 1Hz to 1MHz (3 spectra) is about 1-2 minutes, which is suitable for measurements on human subjects.

Gel electrode

Similar to the Keysight E4990A and Inphaze instruments, the EIS instrument for human subject measurements is considered to be at very low risk when the DC bias is zero and the AC amplitude is at most 1V. Two unique features of the Inphaze system and system are (i) the ability to observe the actual measured AC waveform and (ii) the viewing of the real-time signal-to-noise ratio (SNR) values in the data acquisition software. This allows us to see the quality of the electrodes, whether they are in proper contact, whether they cause signal distortion, or whether there is interference that causes signal distortion. The waveform (not shown) indicates that the signal is very clean, there is no distortion, and the SNR value in the measured data is very good.

EIS systems were evaluated that were versatile and accurate enough to explore various non-invasive device (wearable) configurations (materials, placements, surface areas, etc.) with unknown impedance and unknown test frequency ranges. Several EIS systems on the market were evaluated and the Keysight E4990A instrument was selected. The inventors have also used an EIS system that works well in this application and meets all the requirements. In addition, the system has a very useful utility to view the actual measured signal waveform and SNR in real time, helping to assess electrode performance.

Example 2-electrode design

Research and development was conducted to prototype a suitable front-end for a non-invasive wearable device for a human subject. The front end of the non-invasive wearable device is where the EIS electrodes are in contact with the test participants to non-invasively collect bioimpedance data through the skin. Design considerations for such development include: placing an electrode; fixing the electrode; electrode contact area; wet or dry contact with the skin; the materials used, etc. These factors can influence the ability of the electrode to measure the subject's blood glucose concentration by correlating non-invasive bioimpedance measurements.

Electrode design considerations

Number of electrodes

The non-invasive device for impedance analysis has 4 channels (2 for current and 2 for voltage). The primary benefit of separating the current injection electrode from the voltage sensing electrode when making EIS measurements is that any loading or polarization of the current injection electrode does not affect the voltage sensing performance. No current should flow into or out of the voltage sensing path because only the voltage or potential response of the sample due to the stimulus current should be sensed. Optionally, if signal drift problems are encountered, an additional reference electrode may be used to resolve.

Electrode placement

Bioimpedance measurements are typically made over large segments of the body (i.e., surface area), but some devices operate over smaller areas (e.g., wrists). Obtaining a high quality signal requires good contact over as large a surface area as possible. However, this may need to be balanced according to form factors. For example, if one ring is desired as a non-invasive wearable device, the size of the electrodes will be determined by the minimum electrode size that can achieve a high quality signal.

Electrode orientation

The current source and the current sink are placed at opposite ends of the wearable device. It is contemplated that electrodes may be selected as current source/sink (C) or voltage sense (V) to ensure that the measurement is reliable and accurate. This configuration is shown in fig. 3, where any of 8 positions can be used to insert the electrodes. Ideally, the voltage sensing would be placed at a point between the two areas of current stimulation.

The electrodes may all face the fingers, or the electrodes may be placed externally to facilitate a path from outside the ring to the right hand, to the chest, to the left hand, to inside the ring. The reference voltage may also be used for drift correction.

Manufacture of

The present inventors have manufactured an electrode for use in the present invention. The ideal electrode is small in gauge, dry and can be placed in a housing.

Wet/gel electrode contact

For the purpose of bioelectrical monitoring (EEG, ECG) and stimulation (FES, tES, TENS), gel electrodes may be used to maintain contact. With respect to stimulation, this is because gel electrodes generally exhibit less broadband noise than dry electrodes. Gel electrodes are excellent in assessing the feasibility of bioimpedance corresponding to blood glucose concentrations, as they eliminate any unknown factors in the measurements due to factors that may affect dry contact electrodes.

Gel electrodes were ordered from the same manufacturer and evaluated for consistency and reproducibility when validating the development of the non-invasive device of the invention, as well as for the feasibility of measuring any meaningful signal from a relatively localized area of the body (e.g., forearm or finger).

Electrode material

Substrate (Single)

Materials of relatively uniform composition are considered for their potential ease of use in manufacturing. Several materials were investigated for their efficacy as electrodes. Electrode materials are listed in table 2 as they may be suitable for electrode-skin contact. In the concept verification stage, the entire electrode may be composed of the same material, thereby making it possible to simplify the manufacturing process.

Table 2. materials considered for electrode surface contact.

^aThe lowest cost, $ medium cost, $ $ $ $ highest cost.

As shown in table 2, there are some important properties associated with the material. For example, copper is easily oxidized by the skin when current is applied, thereby compromising the repeatability of the measurement. It is for this reason that copper is not considered as a direct electrode contact material. On the other hand, elements like gold are particularly suitable due to their inertness, but the cost of producing a single piece of gold is high. Since gold is expected as a contact material, alternative methods of coating cheaper conductive materials have been investigated.

Sputter coating

The sputtering coating was studied. This method is less expensive than using pure gold as the electrode material, and can make the electrode shape more diversified.

Electroplating of

Electroplating of gold on other conductive materials was investigated. Several substrates are contemplated, including aluminum, stainless steel, and copper. Soft plating with 24K gold was chosen over hard plating because the gold content of the plating was higher, although thinner. Generally, medical applications use soft plating in contact with the skin due to the higher purity. This coating method is mainly considered due to the high price of gold.

The only problem encountered with electroplating is the quality of the plated product. This may be due to problems with plating techniques, which differ between well plated materials (highly reflective appearance) and "matt" plated materials. Some finishes are easily scratched, while others are very strong.

Fig. 4 shows some variations in the electroplating process, especially on the contact side (closest to the camera).

Bonding

Adhesive coating is also contemplated. Most adhesive options are placed between the conductive metal and the gold plate. Silver epoxy, conductive paint, and the like are used. Some of these conductive adhesives are not durable, however, durability can be optimized and improved. When the electrode of the present invention is coated, the solder performs best in terms of durability of the joining metal. When using gold-plated layers and copper wires, the two are joined together and then fixed to a hollow plastic (nylon) screw with glue.

Comparison of coating methods and materials

Two of the electrode designs that appear to be most promising are gold plated copper and gold plated nylon screws with a banana connector at one end and a gold tab at the other end.

Contact electrode material is an important component for the subsequent stages of prototyping and product development of non-invasive devices. However, gold plating on nylon screws with banana connector configuration was chosen for further validation, since any risk of incomplete copper coverage was reduced considering that the electrode material was pure gold.

Electrode requirements

Repeatability of use

Repeatability of the measurements is important, particularly in the initial stages where the significance of the relevant changes in the signal is unknown. Therefore, robust electrodes are needed to further validate impedance measurements for blood glucose concentration determination. In particular, electrodes capable of withstanding testing for several months without significant changes due to electrode changes are desired.

Size of

There are two competing factors in choosing the appropriate electrode size. The electrode-skin contact area should be as large as possible from a physical point of view, and it should be as small as possible from a wearable point of view.

For the embodiment of the ring as a non-invasive device, consider an electrode contact area of 19mm per electrode²To 36mm². This applies to circular or square configurations of about 5mm to 6 mm. These dimensions are chosen because they are large enough to produce a signal, but small enough not to overlap with a range of potential standard ring sizes. IEC 60601 provides international standards for limiting dc and ac currents with frequencies below 1kHz to 10 ua and for limiting ac currents above 1kHz according to equation 1 discussed earlier.

Example 3 case requirements

Similar devices on the market

For comparison, a carefully selected, commercially available smart ring was purchased. This includes Motiv and G02SLEEP smart rings. Motiv refers to tracking various indicators related to fitness, while G02SLEEP refers to tracking indicators related to SLEEP quality. Another similar product that is not available for purchase (non-invasive, blood glucose monitor) is GlucoTrack, which uses ear clips for measurement.

Whole body analysis

The whole body analysis was studied for the bioimpedance measurements of the present invention. Standard EIS measurements were performed on the whole body using an imprimed device.

Localization

A non-invasive device for measuring a local area of a body is investigated. The electrode configuration tested is typically located in the forearm, hand or finger area. This may be desirable because the locally non-invasive device may be passive in user operation.

Example 4 wearable prototype

Finger ring

Design of

In one embodiment of the invention as a non-invasive device that can be worn on a finger ring. Given the small form factor of the ring, its functional success is most desirable compared to other wearable designs. Figure 5 shows a representation of a ring device.

Referring to fig. 5, a non-invasive device 100 in the form of a ring contains eight electrodes 102 made of gold for contacting the skin. The electrodes 102 are adapted to be connected to a receiver (not shown) mounted within the ring 100 to process the impedance signal. The housing 104 in the form of a ring has eight apertures 106 to accommodate the eight electrodes 102. The electrodes are arranged around the inner circumference of the ring 100 and are spaced apart by approximately 45 ° so that, in use, an electrical current passes through a portion of the subject (i.e. a finger) in use.

In this embodiment, the four electrodes are current injection (stimulation) electrodes and the four electrodes are voltage measurement (sensing) electrodes to measure impedance.

In use, a battery (not shown) is placed in the housing 104. The battery may be non-rechargeable and may be installed/removed through a slot of the housing 104. In other configurations, a rechargeable battery integral to the ring 100 may be used. A charging and/or data port (not shown) may be connected to the ring 100 to allow charging and/or sharing of data with a mobile electronic device such as a computer, tablet, or smartphone.

The ring 100 has a notification indicator 108 to display blood glucose concentration as well as other physiological parameters.

In use, in some embodiments, the device may also wirelessly transmit data to a mobile electronic device, such as a smartphone, for external signal processing and measurement.

The inventors tested a total of 15 different ring designs in this example. These designs can be divided into 6 independent major design modifications, some of which have design similarities between them.

The first design incorporates 8 holes and the later designs focus on the number of electrodes required and the different angular offsets. Later designs included thermocouple space. Later designs focused on electrode placement rather than ring size, as shown in fig. 5 and 6.

Fig. 6 shows different designs of 3D printed wearable housings for rapid prototyping.

Manufacture and assembly

The exact manufacturing process of the housing will generally depend on the electrodes it is adapted to mount. Typically, different housing configurations were printed with black CPE + and water soluble polyvinyl alcohol (PVA) support on an Ultimaker 33D printer. Depending on the electrode to be used and inserted, the preformed hole may be threaded later. The ring may then be sanded and refined. The exact manufacturing process depends on the ring model to be manufactured. After the manufacture of the housing, the relevant electrodes can be inserted.

EIS Performance

An alternative embodiment of a non-invasive device in the form of a wearable finger ring with a 4T (four electrode) ring configuration is shown in fig. 7, with its EIS performance for 7 iterations shown in fig. 8.

For convenience, the numbering of FIG. 7 showing the alternative configuration has been preserved in accordance with FIG. 5.

Referring to fig. 7, a non-invasive device 100 in the form of a ring contains four gold-plated electrodes 102 for contacting the skin. The electrodes 102 are adapted to be connected to a receiver (not shown) via alligator clips 103 to process the impedance signal. The housing 104 in the form of a ring has four apertures 106 to accommodate the four electrodes 102. The electrodes are configured to surround the inner circumference of the ring 100 and substantially oppose each other such that, in use, an electrical current passes through a portion of the subject (i.e. finger) in use.

In this embodiment, the two electrodes are current injection (stimulation) electrodes and the two electrodes are voltage measurement (sensing) electrodes to measure impedance.

In use, the electrode 102 is powered by an external receiver for EIS instrumentation.

As shown in fig. 9, the embodiment of fig. 7 shows good measured signal quality.

Hand ring

Design of

A non-invasive device in the form of a wearable bracelet has also been developed as an alternative embodiment, measuring signals through the wrist of the subject. The "pincer" bracelet design is rigid and allows for fixed positioning of the electrodes on both sides of the wrist to obtain a high quality signal.

The bracelet design allows for maximum electrode-skin contact area. Larger electrodes can be integrated into the bracelet. Notably, unlike the ring or watch design, the electrodes in this embodiment are fixed to the case and cannot be removed without disassembling the electrodes of one embodiment of the invention. A bracelet embodiment is shown in figure 10.

Manufacture and assembly

Similar to the ring, the bracelet was originally printed on an Ultimaker 33D printer. Depending on the model, electrodes, connectors, supports andthe (hook and loop fastener) may have preformed holes, or only the support may have preformed holes, the remaining holes being manually drilled.

After the bracelet is properly cut, the banana connector, which is welded to the copper wire, is inserted into the shell. The loose ends of the copper wires are threaded through and bonded to pure metal pieces that act as electrodes. An adhesive is then applied to the metal piece and bonded to the housing. Followed by supporting the object andadded together and after the adhesive dried, the bracelet was complete.

EIS Performance

The results of 4T bracelet measurements (4 replicates) using the EIS system are shown in fig. 11. Fig. 12 shows the same measurements, but cross-checked by the inphase system (4 replicates).

In the bracelet design of FIG. 10, an asymptote in the phase distribution is observed with two EIS systems at about 30-40 Hz. As shown in fig. 13, the signal quality in the measurement is good.

Watch (watch)

Design of

Non-invasive devices in the form of watches have also been developed as an alternative embodiment, measuring signals through the wrist of a subject. The watch provides an adjustable band.

Watches and bracelets share many similarities, but also have some notable differences. The watch is designed for one side of the wrist only, while the bracelet can be used for both sides of the wrist at the same time. The watch is designed for removable electrodes, while the bracelet uses fixed electrodes. With the popularity of smartwatches in the market, the way to integrate into smartwatches is clear. In addition, the watch has an adjustable band that is snugly and easily adjusted and removed.

For the watch itself, there are 8 holes for removable electrodes compatible with the ring. These 8 holes enable the potential for different electrode configurations. A nearly flush electrode is required to avoid extending too far into the wrist, so an insert is made for an electrode that is not screwed into the watch body. In addition to the electrodes, the wristband of an existing watch may be inserted to secure the watch in place. In later designs, a thermocouple and another insert for a small sensor for measuring physiological parameters were incorporated.

Manufacture and assembly

The watch is convenient to manufacture and assemble. After 3D printing the housing, a watchband can be added and the relevant electrodes inserted.

Conclusion

Various electrode configurations and electrode materials have been developed and tested for non-invasive devices.

Several versions of finger rings, bracelets and watches have been developed, typically with a 4-terminal (4T) electrode configuration, to maximize measurement sensitivity.

It was found that the ring with pure gold electrodes performed well in measuring bio-impedance by finger. It is comfortable to wear and can be repeatedly worn in the same location each time.

Example 5-Electrical Impedance Spectroscopy (EIS) System testing on human Subjects

This example summarizes some of the hard and soft requirements measured in clinical trials on human subjects. The test is a protocol-demanding, labor-intensive, and time-consuming procedure.

Human body test protocol and requirements of wearable device

Typically, during a human clinical trial, test participants will make 10 back-to-back measurements in succession every 10 minutes. This includes (out of order) multiple blood glucose concentration measurements, temperature and pH measurements, heart rate and blood pressure measurements, and 3 types of bio-impedance measurements. The 3 types of bioimpedance measurements are:

imprimed whole body measurements using imprimed SFB7 and imprimed gel electrodes;

4 terminal wrist measurements using imprimed SFB7 and imprimed gel electrodes; and

4 terminal finger measurements using EIS instrument and ring.

The requirements for a non-invasive device for use in a test environment are:

1. measuring time: ideally less than 1 minute due to the compact measurement protocol;

2. signal quality: the better the measured signal quality, the more reliable the data;

3. repeatability: how reproducible the results are under the same conditions;

4. ease of use and comfort: due to the compact measurement protocol, the non-invasive device should be comfortable to wear and easy to connect/operate for long periods of time; and

5. differentiability of EIS data for different blood glucose concentrations.

In order for an EIS instrument to reach a target measurement time of 1 minute, the number of frequencies in the scan, especially low frequencies (<10Hz), or the number of spectra may be reduced. In most commercial EIS instruments, only 1 spectrum is typically measured. To be statistically reasonable, at least 3 spectra should be collected-i.e. each frequency should be measured 3 times. After fine tuning of the EIS system, the measurement time was shortened to a satisfactory 63 seconds (5Hz-500KHz, 3 spectra).

Performance of prototype wearable devices

The data acquisition software of EIS instruments has a unique tool in the form of a "soft oscilloscope" in which discrete data points acquired are plotted against their respective theoretical waveforms (continuous sinusoids). Good measured signal quality means that the discrete points fall exactly on the respective theoretical curve. While soft oscilloscopes provide an instantaneous visual representation of signal quality, noise (mV) provides digital information about signal quality.

The use of these parameters provides a reference point for evaluating the performance of the non-invasive device of the present invention according to the above requirements.

Finger ring

Several ring designs and electrode configurations have been developed and tested to obtain the best performance of bio-impedance measurements by the finger. The design selected for further study is shown in figure 14.

In another embodiment, a 6-terminal ring configuration is also investigated. The 6 terminals are the top i +, v +, i + and the bottom i-, v-, i-, where i ═ current and v ═ voltage. This design has additional current injection electrodes but does not produce any significant improvement in signal quality and repeatability, indicating that the current field distribution is sufficient without additional line pairs, so the 4T configuration is sufficient for human testing because it is physically more convenient to use and manipulate. Figure 15 shows the EIS performance of the optimized 4T finger ring for human testing.

To ensure consistency of the test, the electrodes of the ring were cleaned with isopropyl alcohol and the fingers were shaved and cleaned with a separately packaged skin alcohol wet wipe prior to each measurement.

Hand ring

Bracelet for wrist bio-impedance measurement

Figure 10 shows a photograph of one embodiment of a non-invasive device in the form of a bracelet, wherein the current injection electrodes are 5mm x 20mm pure gold bars, 1mm thick, and the voltage sensing electrodes are 5mm x5mm pure gold squares, 1mm thick.

Like the ring, a 6 terminal bracelet configuration has also been developed. The 6 terminals are the top i +, v +, i + and the bottom i-, v-, i-, where i ═ current and v ═ voltage.

Gel electrode for wrist bio-impedance measurement

The gel electrode of impredimed was also used to measure impedance on the wrist during the experiment. The configuration is shown in fig. 16. Imprimed SFB7 was used as a general EIS instrument, rather than its intended whole-body setup, so body component calculations such as FFM, TBW, etc. were discarded, and only the EIS raw data was retained and used.

Electric interference

During system testing, electrical interference can be seen in some embodiments, such as a "soft oscilloscope". Through a series of system experiments, the interference source is found to come from an extended power panel and a power adapter of a computer and a monitor. The effect of interference is shown in fig. 17. It is clear that the signal data points do not follow their theoretical sinusoidal waveform, and that changes can be observed in real time by moving the power line closer to and further away from the measurement or subject.

To prevent or mitigate interference, the power cord and laptop charger may be relocated away from the measurement site during the trial.

Faraday cage

Design and Assembly

In one embodiment, the faraday cage is a metal box that is large enough to house EIS instrumentation and is also used on a portion of the subject (e.g., the forearm) to accommodate bioimpedance measurements on the fingers/wrist inside the cage. All sides of the faraday cage should be well shorted together (electrically), including the door. The cage has a simple small opening in the back for USB and power cables to pass through.

The frame was constructed using aluminum bars, while the sides and doors were constructed using aluminum sheets. Metal screws and metal butterfly hinges are used to bolt these pieces together while ensuring good electrical contact and conduction. Finally, the faraday cage has several exposed connection points for connecting itself to the analog ground of the EIS instrument. The faraday cage is shown in fig. 18.

Effectiveness of Faraday cages

After a series of test runs, it was found that the faraday cage indeed provides electrical shielding from the power supply line. The power lines have no effect on the signal when measuring passive components (such as resistors and test circuits), as shown in fig. 19. The power cord only affected the ring and bracelet measurements and the faraday cage did provide significant shielding as shown in fig. 20.

The use of a faraday cage can prevent or mitigate signal interference. However, by carefully positioning all power lines and computers in a controlled environment, the effects of electrical interference can be minimized even without a faraday cage.

Conclusion

According to the protocol followed by human trials, the requirements of non-invasive devices are:

1. measuring time;

2. signal quality;

3. repeatability;

4. ease of use and comfort; and

5. differentiability of EIS data for different blood glucose concentrations.

A wearable finger ring was developed and performed satisfactorily in measuring finger impedance during human testing. By rearranging the computers and devices, electrical interference of the power lines is also identified and avoided. Powerful system tests ensure that all components are optimized and that the human body test workflow is as smooth as possible.

Example 6 human body verification

Intention to

A predictive model was developed using a neural network to predict blood glucose concentrations of participants using bio-impedance recorded by electrodes mounted in wearable locations. Initially, Electrochemical Impedance Spectroscopy (EIS) devices currently on the market are used as medical devices to record bioimpedance in manufacturer-defined configurations. These bioimpedance results are then matched to blood glucose concentration measurements to develop a preliminary predictive model of blood glucose concentration prediction based solely on the bioimpedance results.

Participant selection

Three participants voluntarily participated in the study. According to australian liability study behavior guidelines 2018 and the statement of national human study ethical behavior, if an ongoing study is determined to be low risk as part of a formal risk assessment program, ethical review by the human study ethics committee (HREC) is not required. Each process involving human participants was formally risk assessed prior to allowing any experiments.

It was determined that HREC review was not necessary because every process involved in these human baseline experiments was considered low risk. Each participant participating in the project voluntarily participates and provides verbal permission before the ongoing experiment begins. The validity of this process was confirmed in writing by the national institutes of health and medicine (NHMRC) ethical and honesty department and the human ethical office of sydney university. Consideration is made around the personal data collected in the project. Since no HREC review has been performed, all collected data cannot be published publicly. For privacy reasons, the amount of personal information collected is limited and appropriate security measures are taken. All data in this study were compiled, if possible, and each participant was referred to as participant 1, participant 2, or participant 3. If necessary, a single security file may be used to match the participant numbers to their names. Some relevant information about each participant is shown in table 3.

Table 3: participant information on each of the 3 subjects.

Glucose tolerance test

Background

Glucose is the main energy source of the human body. The consumed carbohydrates are broken down into glucose, absorbed by the small intestine, and circulate throughout the body. Insulin is produced by the pancreas and is used to control the transport of glucose to body cells or the liver for glycogen storage (short-term storage) or to promote fat synthesis (long-term storage). Insulin is usually released after a meal to combat elevated blood glucose concentrations.

If blood glucose concentration drops too low, glucagon, another hormone, may be released from the pancreas to release hepatic glucose stores. As discussed above, diabetes is a condition in which the body's ability to produce or react to insulin is impaired, resulting in poorly regulated levels of glucose in the blood. Severe and sudden hypoglycemia (hypoglycemia) or hyperglycemia (hyperglycemia) can be life threatening, causing organ failure, brain damage, coma or death.

Diabetes management is inappropriate with the development of chronic hyperglycemia and progressive damage to organs such as the kidneys, eyes, blood vessels, heart and nerves. Undiagnosed gestational diabetes may result in high birth weight, low blood glucose concentration, and nerve or brain damage in the infant.

Oral Glucose Tolerance Test (OGTT)

Three-step procedure was used for diagnosis of type 2 diabetes: (i) initial risk assessment, (ii) measurement of fasting or random blood glucose levels, and (iii) Oral Glucose Tolerance Test (OGTT). OGTT is the current gold standard for diagnosing diabetes, and is used when the results of fasting or random blood glucose tests are ambiguous (see table 4). All pregnant women were tested for gestational diabetes at 24-48 weeks using OGTT, while women with one or more risk factors (e.g., >40 years, familial diabetes history, certain ethnicities) were tested immediately after confirmation of pregnancy and again at 24 weeks.

Table 4: participants were classified as non-diabetic, requiring an OGTT or fasting or random blood glucose concentration required for diabetes.

OGTT program

OGTT participants should eat normally for 3 days, then fast for 8 hours immediately before testing. Only water was consumed during this fasting period. Smoking or drinking caffeine-containing beverages is not allowed and care must be taken for the drugs, as some drugs (e.g., corticosteroids, beta-blockers, diuretics, and antidepressants) can interfere with the test results. Blood tests (by venotomy) were performed after fasting to record baseline (or fasting) blood glucose concentrations of the participants. A glucose beverage made by Australian Point of Care Diagnostics containing 75g of glucose in filtered water (product number GTT75) was consumed within 5 minutes. Blood was further collected at 1 hour and 2 hour time points. Minimal exercise should be performed during the test and only small amounts of water should be drunk. Blood glucose concentrations were recorded in the pathology laboratory using high pressure liquid chromatography techniques. Results were typically obtained within 2 working days.

OGTT principle

Blood glucose concentration reflects a balance between carbohydrate absorption from the digestive tract, hepatic glucose uptake or export, and peripheral (primarily muscle) glucose uptake. After fasting, the baseline blood glucose concentration of OGTT participants represents hepatic glucose output.

Assuming the participants had a rest during the OGTT, the blood glucose concentrations at 1 and 2 hours after drinking the beverage represent the combination of glucose load and any hepatic glucose output during the test. Blood glucose concentrations at 1 and 2 hours after fasting and drinking of the beverage were associated with the onset of specific microvascular complications of diabetes (retinopathy, nephropathy and neuropathy) and macrovascular complications (atherosclerotic vascular disease), and these values were used as diagnostic criteria for the presence of diabetes.

OGTT results

Diabetes was diagnosed if typical symptoms of diabetes were present if the blood glucose level exceeded 7.0 or 11.1mmol/L, respectively, 2 hours after fasting and/or drinking the beverage (see Table 5). In the absence of symptoms, a second special blood test is required on another day. The diagnosis standards of gestational diabetes mellitus of blood glucose concentration at fasting state and 2 hours after drinking the beverage are 5.5-6.9 and 8.0-11.0mmol/L respectively.

Table 5: in OGTT participants were classified as either fasting or 2 hour post alcohol blood glucose concentration required for non-diabetes, pre-diabetes or diabetes

The OGTT does not distinguish between types of diabetes, predict response to hypoglycemic therapy, or indicate the risk of current or future diabetic complications. Although this test is a gold standard, it is sensitive to incorrect participant preparation, test management, and intra-individual variability. If the results are slightly abnormal and there is a potential impact of incorrect participant preparation or test management, then a duplicate OGTT can be considered.

Glycated hemoglobin (HbA1c)

Diabetes can also be diagnosed by measuring glycated hemoglobin (HbA1c) levels in human whole blood. This measurement is a standard for the modern OGTT in australia. HbA1c is a hemoglobin molecule covalently linked to a glucose molecule. The HbA1c levels in the blood reflect the mean blood glucose concentration over the past 8-12 weeks, not at a particular time point, with elevated levels consistent with chronically elevated blood glucose concentrations.

Therefore, HbA1c levels were measured at any time, even though the participants were not in a fasted state. The HbA1c test is a preferred method for assessing glycemic control in diabetic patients. The limited availability, poor standardization and relatively high cost in many countries balances the utility and convenience of this test. The acceptance threshold for diabetes diagnosis is 6.5% or more (or 48mmol/mol or more), and the diagnosis is confirmed using repeated tests without clinical diabetic symptoms and elevated blood glucose concentration. HbA1c levels in the range of 5.7-6.4% were considered high risk.

Results of clinical oral glucose tolerance test

Throughout this study, clinical OGTTs were performed on participants 1 and 2 as a means of understanding their response to glucose challenge over time and as a means of comparing the accuracy of blood glucose concentration measurements made using the Accu-Chek device with clinical blood glucose concentration results.

Clinical OGTT was ordered by iMedical (an online platform supporting private, customizable blood tests) and was conducted at the lavarty pathology center.

The information collected from the first glucose tolerance test performed on participant 1 was limited because the conventional OGTT test procedure only involved blood testing at 1 and 2 hour time points, while the initial blood glucose concentration measured using the Accu-Chek device rose and declined over a 0-1 hour period, as shown in fig. 21.

Participant 1 was therefore subjected to repeated clinical OGTTs and modified to add blood tests every 30 minutes in a 2 hour test procedure, as shown in figure 22. Likewise, the modified OGTT was also performed on participant 2, as shown in fig. 23.

In each case, the blood glucose concentration values given by the Accu-Chek device tend to be higher than those given by clinical results, often falling outside the error range given by Accu-Chek. The trend of blood glucose concentrations rising and falling sharply to a generally fasting level within the first 1 hour is consistent between OGTTs.

Dual energy X-ray absorptiometry (DEXA)

Dual energy X-ray absorptiometry (DEXA) is the gold standard method of measuring bone mineral density for the diagnosis of disorders such as osteoporosis. It is a non-invasive scan that determines the density of bone and other tissues by sending two low dose X-rays into the body, which are differentially absorbed by bone and soft tissue. DEXA has been commercialized as the gold standard method for measuring body composition, providing information about body weight, body fat percentage and location, and muscle mass and location.

A DEXA scan was performed on participant 1 as a gold standard method of determining body composition, which can then be compared to body composition analysis using an impredimed impedance device. A key result from this DEXA scan that can be used to compare to the imprimed impedance results is that the overall percentage of fat for participant 1 was calculated to be 19.7%, as shown in table 6.

Table 6: analysis of body composition of participant 1 as determined by DEXA.

Blood glucose concentration monitoring

Error grid type

Monitoring blood glucose concentration is an important component of diabetes management, and treatment decisions can be informed to improve the prognosis of diabetic patients. There are many different devices available for monitoring blood glucose concentration, each of which must be validated against multiple metrics before being qualified for marketing.

ISO 15197:2013 defines that for glucose concentrations below 5.5mmol/L the device 95% blood glucose results need to be within. + -. 0.8mmol/L or for glucose concentrations equal to or above 5.5mmol/L the device 95% blood glucose results need to be within. + -. 15% compared to the reference laboratory method. In addition to this requirement, 99% of the blood glucose concentration values must lie within zones a and B on the Parker Error Grid (PEG) generated for type 1 diabetes management. As described below, there are 3 major error grid types used to monitor device performance for BGL monitoring.

Conversion of mg/dL to mmol/L

There are two units used to quantify blood glucose concentration: mg/dL and mmol/L. Different systems are used in different parts of the world. The specification in Australia is mmol/L, while in the United states, the specification is mg/dL. This means that most diabetes literature is in mg/dL units and requires conversion to mmol/L for use in Australia. The conversion from mg/dL to mmol/L is shown using equation 2.

Where BGL is blood glucose level (equivalent to blood glucose concentration).

Clark Error Grid (CEG)

Clark Error Grid (CEG) was fabricated by 5 experts at the university of virginia according to their clinical practice as the original error grid fabricated for monitoring device performance. This error grid compares the reference BGL (x-axis) to the BGL determined by the monitoring device (y-axis) to qualify device performance, where each region into which a data point may fall has a defined meaning:

and a region A: represents no effect on clinical effects;

and a B region: represents an altered clinical effect but has little or no effect on clinical outcome;

and a C region: representing altered clinical effects and possible effects on clinical outcome;

and (3) region D: represents an altered clinical effect that may have significant medical risk; and

and a region E: representing altered clinical effects that may have dangerous consequences.

CEG is shown in FIG. 24.

Pax Error Grid (PEG)

Pax Error Grids (PEG), also known as consensus error grids, were proposed in 2000 to replace CEG. It was proposed by 100 physicians at the american diabetes association annual meeting to solve some of the problems prior to CEG: (i) CEG was proposed by only a few experts, (ii) there was a discontinuous transition between zones, (iii) there was no distinction between type 1 and type 2 diabetes. Two different PEGs were created for type 1 and type 2 diabetes, respectively, the main difference being the a and B zones at low glycemic concentration values, as shown in figure 25. Nevertheless, the PEG for type 1 diabetes is the most commonly used and the only error grid covered in ISO 15197: 2013. This is the type of error grid used throughout the study.

Monitoring error grid (SEG)

Monitoring error grids (SEGs) were proposed in 2014 and were developed by several authors in the self-learning, industrial and regulatory communities. It was constructed using a survey conducted by an interview team consisting of 206 clinicians and 28 non-clinicians, where each person created their own error grid and then merged the grids. It provides a continuous risk level of hypoglycemia or hyperglycemia from green (low risk) to red (high risk) aimed at helping regulatory agencies and manufacturers assess the risk of blood glucose concentration monitoring systems encountering problems in the post-market environment, as shown in fig. 26. Although this is the most recently developed error grid, it does not allow for quantification of data points within different regions and is therefore not used in this study.

Blood glucose concentration/level (BGL) monitoring in prior studies

Several published studies were analyzed to understand the range of BGL values obtained during testing of different populations. In each case, the actual and measured BGL ranges from 0mg/dL (0mmol/L) to 500-600mg/dL (28-33mmol/L), with typical data points ranging in concentration from 50-300mg/dL (3-17 mmol/L). Some representative graphs and participant conditions are included in FIG. 27. Since all 3 participants participating in the program had no diabetes, the range of BGL expected to be obtained was limited, and BGL manipulation (e.g., using GTT) was required to maximize the range possible.

Preliminary blood glucose concentration/level (BGL) monitoring in this study

Initial experiments in this study were aimed at providing sensing of results expected from conventional BGL monitoring before the BGL measurements were matched with bioimpedance data to generate a preliminary predictive model. BGL measurements were initially made on participant 1 alone over 4 days using both Accu-Chek and Freestyle library devices to compare performance between the devices.

These data were then combined with the initial BGL data for participant 1 and participant 2 collected from the simultaneous BGL and bioimpedance measurements to expand the dataset compared by the Accu-Chek and Freestyle Libre devices.

When comparing the BGL results obtained from each of the two devices simultaneously in the PEG map, all data points fall within the a region, as shown in fig. 28. This indicates that each device performs well with respect to each other despite the expected time delay of the Freestyle library device.

Preliminary bioimpedance results in this study

All bioimpedance measurements performed as part of the human baseline experiment in this study were performed using an impredimed impedance device. In these human baseline measurements, most of the data was collected throughout the body according to the intended use of the impredimed device. The first set of measurements is made to assess the consistency of the device. Participant 1 was measured at time points around the meal. Five measurements were taken at each time point, automatically at 5 second intervals. The reactance and resistance results were consistent across all 5 measurements taken at a single point in time, but there was a difference between measurements taken at different points in time, as shown in fig. 29.

Additional baseline data was collected through the whole body using an imprimed device with imprimed gel electrodes attached to the forearm (upper and lower sides) and a 1cm long strip of imprimed gel electrodes attached to the finger as shown in figure 30. In each configuration, a kohler diagram (resistance versus reactance) and a diagram of reactance versus frequency and resistance versus frequency are generated and displayed to provide an example of a typical curve to ensure similar results are obtained during device use, as shown in fig. 31.

Simultaneous blood glucose concentration and bioimpedance measurements

To develop a preliminary prediction model to predict blood glucose concentration based on bioimpedance measurements, the bioimpedance data must be collected at the same time that the blood glucose concentration data is collected. Whole body bioimpedance was recorded using an imprimed device and the corresponding gel electrodes were placed according to the device operating instructions, as shown in figure 32.

The position of electrode placement is consistent between measurements and a new gel electrode is used for each measurement, even if measurements are recorded over a narrow period of time separated from each other. The contour of each electrode is tracked with permanent markers to ensure that the electrodes are always placed in the same position. The electrode placement position is not shaving prior to placement. For each time point, 5 different measurements were made at automatic 5 second intervals using an impredimed device.

During these bio-impedance measurements, the skin temperature is recorded as an auxiliary physiological parameter. A thermocouple was placed in close proximity to the electrode placement and the skin temperature was recorded using a ThermaQ device. Thermocouples were placed 2cm below the hand and sole electrodes, towards the fingers or toes. The thermocouple was covered with a folded paper towel for insulation.

Blood glucose concentration measurements were made using Accu-Chek and Freestyle Libre devices as close as possible to the time of the corresponding bioimpedance measurements. This data is entered into the main Excel document along with the bioimpedance results (the korotkoff fitting parameters and raw data for each of the 5 measurements taken at a single time point) and the temperature measurements, each time point corresponding to the time at which the Accu-Chek measurements were taken. The first round of data collected 7 days of data for participant 1 and participant 2. The second round of data collection is done as a temporally distinct set of data for independently validating the preliminary predictive model developed using the results of the first round of data collection. Data was collected from participant 1, participant 2, and participant 3 during these measurements, with participant 1 and participant 2 data used as the different sets at that time for independent validation, and participant 3 data used to test how effective the preliminary predictive model was on participants whose data was not exposed to the neural network.

This data is used as input to a preliminary prediction model to predict blood glucose concentration based on the systemic bio-impedance results, which is then compared to actual blood glucose concentration measurements.

A graph was plotted for each participant comparing the blood glucose concentration (Accu-Chek) over a range of frequencies with the bioimpedance for all data collected in this experiment. There is no clear trend to indicate a direct relationship between blood glucose concentration and bio-impedance, which supports the use of neural network models to correlate these inputs. An exemplary diagram of each of participant 1 and participant 2 is shown below, as shown in fig. 33.

Once all data is collected for this data set, the mean and range for each parameter is determined to inform the expected range for these parameters in future experiments. These are calculated and displayed as blood glucose concentration (Accu-Chek, Freestyle Libre), temperature (hands, feet), body moisture content and fat percentage.

Example 7 preliminary prediction model

Intention to

A preliminary predictive model was constructed to determine whether it was possible to correlate bio-impedance measurements (BI) with blood glucose concentrations/levels (BGL) from study participants of the human baseline study described in example 6. Artificial neural network modeling methods have been chosen for this purpose because neural networks are able to identify hidden correlations and are considered to have sufficiently flexible architectures and parameters to continue to improve the model.

The minimum requirement for the model success criteria is that the model be able to predict BGL such that at least 70% of the results are located in region a and region B based on the Pax Error Grid (PEG) region. Furthermore, it is desirable that the model be able to track BGL trends over time.

The initial modeling work is based onThe impedance measurements taken by the device are,the device used an attached standard gel electrode and was evaluated systemically as a standard for assessing body composition.The SMBG meter is used to take needle BGL readings for use as a reference for training and testing the model.

The modeling work performed at this stage was then used to inform the design of human trials and the development of the predictive model described in example 9.

Data analysis Using R

The R language was chosen for this study because of its advantages including open source license availability, relatively few cross-platform issues, extensibility through multiple package options, useful support documentation, and strong user community support. The RStudio IDE is used for encoding in R.

The "neuralenet" package was used for neural network modeling, and additional packages used in the code are shown in table 8.

Table 8: r-package for use in model development derived from source code

Source data

Data description for modeling

FromThe bio-impedance data obtained by the device includes raw values and subsequently processed fitting parameters. Furthermore, the following auxiliary data were measured during the test:

participant height;

participant weight;

age of the participant; and

participant gender.

FromThe bioimpedance data obtained by the device were as follows:

raw data of reactance and resistance at 256 frequencies:

frequency (kHz), also called F in the raw data;

resistance (ohms), also called R in the raw data; and

reactance (ohms), also called X in the raw data.

The device that generated the fitting parameters processes the data:

frequency (kHz), also called F in the raw data;

kohl fitting center X, ohms;

kohl fitting center R, ohms;

kohler radius, ohms;

SEE radius,% R (zero), ohm;

r (infinity), ohm;

re, ohm;

ri, ohm;

z characteristic, ohm;

f characteristic, kHz; and

membrane capacitance, nF.

Human baseline data used were collected over 2 weeks. Data was collected for the whole body configuration. It should be noted that during this initial stage of the encoding process, the patient height, patient weight, patient age and weight index series need to be removed from the data set due to scaling errors when attempting to use the subject 3 data set for testing. This scaling problem is due to the separate scaling of the training and test data sets, which is later circumvented by using standardized scaling methods (discussed later).

There were a total of 250 rows of data, with 5 impedance results per BGL data point obtained due to the repetition in the data collection process. The data set utilizes the above-described apparatus to process data fitting parameters.

Data scaling

Due to the algorithm used, the data set needs to be scaled numerically for use with the neural network package.

In the preliminary modeling, the scaling method is as follows:

1. identifying a maximum and a minimum of the data set;

2. the data range is calculated as the difference between the maximum and minimum values; and

3. a data box scaled centered on the minimum value set using the range calculated above.

Two improved scaling methods (normalization and normalization) were explored at a later stage of model development, as described later in example 9.

Neural network design

Model and architecture description

A two-layer neural network model with 3 nodes in each layer is used in the neural network model. Two hidden layers are used to allow greater model flexibility and increase the likelihood of finding a correlation in the data than if one hidden layer is used. Two layers were used as upper limits to avoid overfitting. Three nodes per layer were selected for initial testing and then changed during the stage of evaluating model performance.

Activating a function

The activation function is a differentiable function for smoothing the cross product results of covariates or neurons with weights. By default, a linear activation function ("TRUE" in neural network code) is used, but a hyperbolic tangent and a logistic function may also be used.

Training and testing

The complete data set was split at approximately 80:20 between the training set and the test set, and the data points were randomly selected. At this stage, the data distribution is not evaluated to ensure that the test set represents the model. For example, we did not evaluate the number of test values used by each participant.

Model training employs an improved K-fold cross validation technique to improve the robustness of the model. 5-fold cross validation was performed, with 5 training and validation of the model. For each round of training, the training set was randomly split at 60-40 between training and validation. I.e., 60% of the data for training and 40% for validation, using a different data set for each round of training.

This is slightly different from the standard K-fold implementation, for 5-fold validation, at 80:20 split, with 20% being system-selected so that at the end of training all data points are used for training and validation. Currently used methods do not ensure this, but rather increase the validation set to minimize the amount of data that may not be used for validation.

Randomness within the model is implanted to ensure reproducibility of results between test runs, as well as across different computers on which the test is performed.

Evaluating model performance

Mean Square Error (MSE)

Mean Square Error (MSE) measures the mean squared error between the predicted and actual values, and is calculated as fair

And formula 3.

It should be noted that the positive sign of MSE due to the squaring of the molecules removes potentially useful information about the deviation of the prediction result from its actual counterpart.

Mean Absolute Relative Difference (MARD)

The Mean Absolute Relative Difference (MARD) is a general measure of accuracy typically used in blood glucose measurement analysis, often referred to in describing the performance of CGMs. It is the average difference between the predicted value and the actual value, as opposed to the actual value itself, and the calculation is as shown in equation 4.

There are many limitations and disadvantages to using MARD as a primary indicator of model performance. It should be noted that while a lower MARD value indicates a better fit than a higher MARD value in a data set, it is difficult to directly compare MARD values between different data sets due to factors such as data range and collection method.

It is also possible that during a comparison, a result with a lower MSE may have a higher MARD, requiring an additional basis for comparison, such as the parker error grid discussed below.

Pax Error Grid (PEG) region

Ideally, the predicted blood glucose concentration value from the model will almost exactly match the actual blood glucose concentration value obtained from the lancing device with a relatively small error. The Pax Error Grid (PEG) is a conventional way to describe the comparison of the predicted value to the actual value of a blood glucose concentration measurement. The data will fall into one of five regions, a-E based on potential clinical impact, with region a having no impact and region E having significant clinical impact. The proportion of points in each region is quantified during reporting. For example, in FIG. 34, the data point was 89% in the A region, 7% in the B region, and 4% in the C region.

A detailed discussion regarding the use of an error grid for blood glucose concentration prediction is provided under the heading "error grid type" above.

Model analysis (results)

Basic implementation

Work in this study refers to initial human baseline modeling to assess the suitability of modeling blood glucose concentrations using bioimpedance data.

The model uses two hidden layers, three nodes per layer, 5-fold cross validation and 60-40 training-validation scale splitting. The results are summarized in Table 9. In general, the model, when attempting to model using measurements from the whole body and wrist, can use bio-impedance (fitting parameters) to predict blood glucose concentration: 100% of the PEG spots were located in the a + B region for both training/validation and testing.

Table 9: neural network model realization of whole body Sprint 3 data

Modeling using raw frequency data

Improving neural network model implementation in accordance withPredicting the blood glucose concentration using the raw bio-impedance (BI) values of (b), in particular:

frequency (kHz), also called F in the raw data;

resistance (ohms), also called R in the raw data; and

reactance (ohms), also called X in the raw data.

Using R and X values between 10-500kHz, andand the frequency range values used when the post-processing result is viewed by the user are kept consistent. The total number of points is 256, and 84 are discarded outside the frequency limit, so that 172R points and 172X points are used for modeling. The results are shown in Table 10.

Table 10: results of modeling using raw frequency data.

^aMSE is mean square error;^bMARD is the average absolute relative difference; and^CPEG ═ PaA grid of gaussian errors.

The results show that the concept of using bioimpedance to predict blood glucose levels within the parameters and data sets of the present study still has potential feasibility when attempting to model using raw output results (i.e. F, R, X) rather than device processed values (e.g. kouer resistance): for all cases studied, most of the points were located within the a and B PEG regions.

Based on the above findings, further evaluation of the predictor variables was attempted, in particular, to sub-set the frequency points for training/validation and testing. The results are shown in Table 11.

Table 11: results of modeling using a subset of raw frequency data

The concept of using bioimpedance to predict blood glucose levels within the parameters and data sets of the present study still has potential feasibility when attempting to model using raw output results (i.e. F, R, X) rather than device processed values (e.g. kouer resistance): for all cases studied, most of the points were located within the a and B PEG regions. Interestingly, in some cases, model predictions were improved using less data, which may be due to outliers at some frequencies.

Using a subset of the original frequency data: median value

Overall, it was found that using median values for each unique combination of date, time, participant and blood glucose concentration provided a reasonable prediction of blood glucose concentration values. The training results for median have higher MSE, MARD and lower PEG region accuracy than when all values are used instead of just taking the median.

On the other hand, the test results using median values show a slightly lower MSE but a slightly higher MARD than the former. In addition, the test when the median was used had a slightly higher percentage of B-zone, a slightly lower percentage of a-zone, and a percentage of no C-zone (but not the median was used with a small percentage of C-zone). The results are shown in Table 12.

Table 12: results using a subset of the original frequency data (median)

Thus, it is believed that the method of obtaining the median value in each data subset prior to modeling may be undesirable, and that finding all rows that utilize the obtained data is the preferred method of future modeling.

Evaluating the effects of "noise" data

By studying the resulting variation in the predictive power of the model, studies were conducted to understand the effect of introducing "noise" into the data. To this end, the 10% data set was modified (i.e., error introduced) by replacing with random blood glucose concentration values of 1 to 10 mmol/L. The results of this analysis are shown in table 13.

Table 13: the result of introducing "noise" into the data set

In general, the concept of using bio-impedance to predict blood glucose concentrations within the present reported parameters and data set remains viable even when errors are introduced during the training/validation phase. There was no noisy data during training/validation, and 100% of the points continued to fall within the A and B regions of the PEG plot for modeling in training/validation and testing (using data not previously shown to the model) in the test cases.

Using noisy data during training/validation, predictability decreased as expected compared to no noisy data, with some points falling within the C region of the PEG map and error values increasing. However, for the test cases, both prospective and unexpected trends were observed, with improved results for participant 2 compared to when tested using a model trained based on the raw data.

It was also found that when tested using a model that had been trained and validated using data from participants 1 and 2, the MSE and MARD of participant 3 increased while maintaining a similar PEG zone ratio as compared to using only noise data from participant 1. Thus, training and validation using one participant may result in varying degrees of predictability of blood glucose concentration among other participants.

Conclusion

In general, the concept of using bio-impedance (BI) to predict blood glucose concentration within the parameters and collected data of the present study was found to be feasible. Can use the method fromThe raw output of the device (i.e., F, R, X) and the device processing values (e.g., kouer resistance) to predict blood glucose concentration, for the reported case, typically have 100% prediction in the a and B Pax Error Grid (PEG) regions.

The constructed neural network model is found to meet the expected purpose and exceeds the research success standard of 70% of prediction points in the areas A and B on the Pax error grid.

EXAMPLE 8 human testing

Intention to

From the bioimpedance measurements taken systemically using the imprimed SFB7 device and corresponding gel electrodes, a preliminary prediction model was developed to predict blood glucose concentration/level (BGL), as discussed previously.

The objective of the human test experiment in example 6 was to develop an accurate predictive model after learning from a human baseline experiment and development of a preliminary predictive model. This includes incorporating broader auxiliary parameters (such as physiological parameters) as inputs into the neural network to move the location of electrode placement on the body to a location suitable for non-invasive wearable devices (wrists, fingers), and bioimpedance recordings using EIS instruments.

Method

Development of skin pH measurement

Experiments were performed to understand the skin pH of participants at different times and under different conditions before establishing the final human testing protocol. The pH values of the different areas of the body (feet, hands, arms) were found to be approximately consistent over the course of 3-4 hours.

The pH measurements on the arm remained generally consistent on different days, while the pH of the hands appeared to fluctuate most with different treatments of the hands (e.g., washing), while the pH of the feet appeared to fluctuate with the production of sweat.

The effect of adding some creams (e.g. moisturizers) is small, while the effect of adding other creams (e.g. sunscreens) is greater. Cleaning the pH measurement site with an isopropyl alcohol wet wipe gave the most consistent results and was preferred prior to measurements in the human test protocol.

Wrist bio-impedance development

Before deciding to use impredimed with gel electrodes on the wrist, experiments were performed to confirm that this configuration was feasible and produced reproducible results. The gel electrodes are placed in a position below the protruding bones protruding from the wrist, as placing the electrodes on the bones results in poor results.

In the following days, measurements are taken over an extended period of time, with the same positioned electrode being removed and replaced in a different measurement. These results show that the acquired data has a significant (visible) reproducibility in each measurement and that this configuration is decided to be suitable for introduction into human testing.

Final body test protocol

The human test protocol is intended to include a wider range of parameters to be measured than the human baseline experiment. The same 3 participants described previously were also involved in these experiments. The measured parameters were:

1. a bio-impedance;

a. whole body (imprimed, gel electrode);

b. wrist (imprimed, gel electrode); and

c. finger (EIS instrument, dry electrode in ring device).

BGL (blood glucose concentration/level);

Accu-Chek; and

b.Freestyle Libre。

3. skin temperature (4 locations);

4. skin pH (4 sites);

5. blood pressure (systolic and diastolic); and

6. heart rate.

Whole body bioimpedance was recorded using an imprimed device and gel electrodes in order to benchmark the results of this experiment to a preliminary predictive model.

Bioimpedance on the wrist was recorded using an imprimed device and gel electrodes with the aim of transitioning towards a position on the body suitable for a non-invasive wearable device, but using EI instruments and electrode systems proved suitable for BGL prediction using a neural network model, as shown in fig. 16.

The use of an EIS instrument and a prototype dry electrode to record the bio-impedance of a finger with the aim of moving towards a position on the body suitable for a wearable device, and the use of a prototype EIS device and dry electrode combination, which may be suitable for a non-invasive wearable device, is shown in fig. 35.

All electrodes were left in place for all bioimpedance measurements performed in a single run of the test protocol. The position of the electrode placement is consistent between different runs of the test protocol. The outline of each gel electrode was traced in a permanent mark and each position where the electrode was placed was photographed to achieve this, as shown in figures 36 to 38.

The position of the ring for finger bio-impedance measurement is kept consistent by placing the ring as far as possible below the middle finger and ensuring that the electrodes are in full contact with the same location on the participant's finger. Permanent markers are used to guide placement of the ring and indicate the electrode placement position, as shown in fig. 39.

Before placing the gel electrode on the wrist and the ring on the finger, the shaving electrode contacts the site to remove all hairs. The electrode placement position for the whole body measurement was not shaved as this had not been done before during the human baseline experiment. The gel electrodes were held in place with paper tape to ensure that they did not move throughout the test protocol and that proper electrode contact was maintained. A small piece of tape (about 5cm) was passed through each gel electrode on the hand and foot where a whole body measurement was taken, and a piece of tape was wrapped around the entire wrist where the gel electrode was placed for measurement through the wrist.

A series of secondary physiological parameters are measured along with the bio-impedance as these may affect the bio-impedance data collected: skin temperature near the electrode placement site, skin pH near the electrode placement site, systolic and diastolic blood pressure, and heart rate, as shown in fig. 40.

Measurements were made near the electrode placement site for skin temperature and skin pH, and the measurements described below are shown in table 14.

Table 14: skin temperature and skin pH measurements

Data was recorded for each of the 3 participants during 8 OGTTs (total OGTTs 24) over a 5 day test period. This OGTT procedure involved drinking a glucose solution (75 g glucose added to 300mL water; from POCD Scientific) and measuring all parameters at 0, 10, 20, 30, 40, 50 and 60 minute time points after drinking.

Measurements were taken at the 0min time point of the recorded time before drinking the beverage. The timer was started immediately after drinking the beverage and each set of measurements was taken after the timer reached 10, 20, 30, 40, 50 and 60 min.

The measurements are carried out in the following defined sequence, so that the time points of each measurement of a specific parameter are approximately the same:

1. skin pH (0 min);

a. a foot;

b. a hand;

c. a wrist; and

d. a finger.

2. Bioimpedance-whole body;

3. skin temperature-whole body;

4. bioimpedance-wrist;

5. skin temperature-wrist;

6. bioimpedance-finger;

7. skin temperature-finger;

8.BGL-Accu-Chek；

9.BGL-Freestyle Libre；

10. blood pressure and heart rate; and

11. skin pH (60 min);

a. a foot;

b. a hand;

c. a wrist; and

d. a finger.

Due to the varying length of time required to perform skin pH measurements, only 0min and 60min were performed, since there was not enough time in the test procedure to reliably accommodate every 10min of measurement. This means that the data cannot be used as input to the neural network model.

No caffeine was ingested prior to or during the test procedure (unless otherwise stated) and, where possible, the first measurement of the day was recorded for participants who fasted overnight. Data for each measurement is manually entered into a table and then scanned and backed up to the cloud. For the bio-impedance measurements, the data file name is recorded, along with the data values for each of the other parameters. The finger punctured to make the Accu-Chek measurement is recorded in the appropriate column and any relevant comments are recorded in the last column. The exact time of each measurement is also recorded in the appropriate field.

Data from each OGTT is entered into a master Excel document according to the test program. The ImpediMed data file is uploaded from the device and copied to the cloud. The data is batched in the imprimed software to generate a spreadsheet containing all the calculation parameters associated with each data file, as well as additional spreadsheets for each data file containing the raw data. The calculated data was manually copied into the main Excel document, and the raw data (resistance and reactance values at each frequency of analysis) corresponding to each data file was copied into the main Excel document using the macros embedded in the document. Data generated by the EIS instrument is also backed up to the cloud, and the data in these files is also copied into the main Excel document using macros embedded in the document. At the end of each day, the following tasks were completed:

1, uploading the ImpediMed data to a cloud;

uploading EIS instrument data to a cloud;

3. inputting all data in the printing data table into Excel, and scanning and storing;

4. downloading and backing up Accu-Chek and Freestyle library data of each participant;

5. inserting equipment needing charging to switch on a power supply;

6, storing the pH probe overnight;

7. arranging a test area;

8. emptying the garbage can; and

9. the consumables for the next day are prepared.

At the beginning of the day, the following tasks are completed:

1. testing imprimed using a test unit (the device is required to pass the test before it can be used in human participants);

2. testing EIS instruments using standard resistors (required to pass the test to use the device for human participants);

3. testing the ThemaQ equipment;

4. testing the sphygmomanometer; and

5. the pH probe was calibrated.

Before each test, the following tasks are completed. To speed up the testing process, the testing process is completed for the previous participant while tasks 2-5 are completed:

1. the dry electrode was washed with isopropanol. This was to ensure that there was no residue on the electrodes from the previous round of testing.

2. The participants went to the toilet. This is to empty their bladder, which might otherwise affect the bio-impedance measurement. Ideally, this should be done before each whole body bio-impedance measurement throughout the test, but due to time constraints this is not possible in this experiment.

3. All items were removed from the participant's pocket and any jewelry/metal was removed (e.g., a belt with a metal buckle). Objects or metal objects may affect the bio-impedance measurement.

4. The skin of the participants was cleaned with an isopropyl alcohol wet wipe at the electrode placement site.

5. The gel electrode was placed and secured in place with tape.

6. And fixing the sphygmomanometer cuff. It is placed on the other arm of the participant, opposite the arm to which the Freestyle Libre device is applied.

7. The ring and the electrode are fixed on the finger.

8. A thermocouple was connected. These were taped in place and covered with a folded paper towel (also taped in place) to increase insulation. The thermocouple placed under the ring was uninsulated.

9. The EIS instrument is tested for proper response.

The following checklist is used to ensure that all tasks have been completed at the beginning of the day, before each test, during each test, and at the end of the day.

To avoid the problem of incorrect lead placement, guidance as in fig. 41 may be provided to illustrate the correct lead placement and configuration.

Results

Using the OGTT to manipulate participant BGL, a broader BGL was obtained than the data input to the preliminary predictive model, as shown in Table 15. The range, mean, median and rate of change of BGL varied from participant to participant.

Table 15: the range, mean, median and rate of change of BGL measured using an Accu-Chek or Freestyle Libre instrument for participants 1, 2 and 3.

Once all data is collected for this data set, the mean and range for each parameter is determined to inform the expected range for these parameters in future experiments. These are calculated and displayed for BGL (Accu-Chek, Freestyle Libre, OGTT), skin temperature (hand, foot, wrist, fingers), skin pH (hand, foot, wrist, fingers), blood pressure, heart rate, body moisture content and fat percentage.

Example 9 prediction model

Intention to

As discussed above, it was found that predictive models can be used to correlate bio-impedance measurements (BI) of study participants with blood glucose concentrations. The artificial neural network modeling methods used in this study were extended and modified because they were able to identify hidden correlations and had sufficiently flexible architectures and parameters to continue to improve the model.

The minimum requirement for the model success criteria is still the ability of the model to predict BGL such that at least 70% of the results are located in region a and region B based on the Pax Error Grid (PEG) region.

This modeling work is based on a model fromDevices and EIS instruments obtain impedance measurements in whole-body, wrist, and finger configurations. For the sake of consistency,the SMBG meter is used to obtain needle BGL readings as a reference for training and testing the model. This modeling work uses data obtained during human trials and has been used to inform subsequent model development decisions.

Source data

FromThe whole body and wrist configured bio-impedance data obtained by the device includes raw values measured by the device and processed fitting parameters. FromThe data obtained by the device includes:

raw data of reactance and resistance at 256 frequencies:

frequency (kHz), also called F in the raw data;

resistance (ohms), also called R in the raw data; and

reactance (ohms), also called X in the raw data.

The device that generated the fitting parameters processes the data:

kohl fitting center X, ohms;

kohl fitting center R, ohms;

kohler radius, ohms;

SEE radius,% R (zero), ohm;

r (infinity), ohm;

re, ohm;

ri, ohm;

z characteristic, ohm;

f characteristic, kHz; and

membrane capacitance, nF.

From EIS instruments, the following information is used to model finger configuration:

z (impedance), ohms;

phase (angle), degree;

g (conductance), siemens; and

c (capacitance), farad.

In addition to the bioimpedance data, the following auxiliary data were recorded during the test:

participant height;

participant weight;

age of the participant;

participant gender; and

skin surface temperature.

Data were collected over 3 days. Participant 1 and participant 2 each had 42 samples and participant 3 had 28 samples. For each BGL data point obtained from the whole body and wrist, 5 impedance results correlated with the value due to the repetition in the data collection process. Each BGL value has 3 impedance results.

Data scaling

Due to the algorithm used, the data set can be scaled numerically for use with the neural network package. Two possible scaling methods were explored:

normalization: the values are rescaled to a range of 0 to 1, including 0 and 1. This approach is often useful when the parameters need to have the same positive proportions, but outliers in the data set are lost; and

normalization: the mean of the data was rescaled to have a mean of 0 and a standard deviation around the mean of 1.

Normalization was chosen to avoid automatic discarding of outliers, since visualization and manual decision making based on the spread of data was deemed necessary. For this purpose, the "dataprediction" package in R was chosen.

In this package, the "build scales" function is used to calculate the scale to use from the training data set. From that point on, the "fastScale" function is used to scale the training dataset, followed by the test dataset based on the former.

Model information

As with the preliminary model, a two-layer neural network model of 3 nodes per layer is used in the present neural network model. A linear activation function is used. The complete data set was split at approximately 80:20 between the training set and the test set of each participant, and the data points were randomly selected.

Randomness within the model is implanted to ensure reproducibility of results between test runs, as well as across different computers on which the test is performed.

5-fold cross validation was performed, with 5 training and validation of the model. For each round of training, the training set was randomly split at 60-40 between training and validation. I.e., 60% of the data for training and 40% for validation, using a different data set for each round of training.

Model performance was evaluated by calculating the Mean Square Error (MSE), Mean Absolute Relative Difference (MARD) and ratio of predicted points within the Pax Error Grid (PEG) region.

Model implementation

The modeling results are shown in table 16.

Table 16: neural network modeling results from the whole body, wrist and finger data of study participants 1, 2 and 3.

In general, for a gene fromWhen trying to model by whole body and wrist measurements, the model can use bio-impedance (fitting parameters) to predict blood glucose concentration: 100% of the PEG sites are located in the a + B region, including additional physiological parameter measurements outside the BI (e.g. temperature, heart rate) improves the predictive power.

Furthermore, for the case of finger data from EIS instruments, the model can also predict blood glucose concentration using raw bio-impedance values: almost 100% of the PEG points are located in the a + B region, including auxiliary physiological parameter measurements outside the BI (e.g., temperature, heart rate) improves the predictive power of the training dataset rather than the test dataset.

Conclusion

In general, the concept of using bio-impedance (BI) to predict blood glucose concentrations within the present study parameters and collected data remains applicable to the use of information fromAnd full body, wrist, and finger configurations of data for EIS instruments.

It can be concluded that the constructed neural network model meets the expected purpose, exceeding the research success standard of 70% of the prediction points in the areas a and B on the pax error grid.

Example 10 Pre-market Spot/early feasibility study

Intention to

After collecting BGL data for participant 1 and participant 2 as part of human baseline measurements, it was noted that only a limited range of BGL values were obtained (4.1-8.9 mmol/L for participant 1 and 4.4-6.5mmol/L for participant 2 according to Accu-Chek), all in the population without diabetes.

Although the test procedures were modified to extend the range of BGL values obtained prior to testing in humans, the ideal approach was to recruit poorly managed diabetic patients who would be expected to produce broader BGL values.

The possibility of conducting pre-market pilot/early feasibility studies in the current study period was explored, taking into account the time frame to complete all the requirements.

BACKGROUND-clinical trials of medical devices

Clinical trials of medical devices are conducted through "stages" rather than "phases" which include:

pre-market trial: 10-30 participants. Exploratory surveys to gather preliminary clinical safety and performance information to guide equipment modification or to provide support for future critical research. After other non-clinical tests (engineering analysis and testing, computational simulation, biocompatibility testing and, where appropriate, animal testing). First included human and feasibility or concept validation studies.

Key pre-market studies: 100+ participants. Confirmatory investigations to assess equipment performance and safety for specific intended uses to meet pre-market regulatory requirements.

After marketing: 1000+ participants. For establishing confirmatory surveys of performance and safety in a broader population, or for observational surveys to better understand equipment safety, long-term outcomes, and health economics.

Details of the experiment

Details of the pre-market pilot/early feasibility study investigated as a possibility in the current study period are as follows:

the purpose is as follows: a more extensive BGL recording is achieved by recording data of diabetic participants to augment the neural network model associated with BGL and bioimpedance.

The participants: 10 adults between the ages of 18-50 years, who have been diagnosed with type 2 diabetes in the last 10 years. Participants with HbA1c ranging between 7-8.5% prefer participants with suboptimal oral management.

Experiment: participant BGL (using Accu-Chek mobile device) and bio-impedance were recorded simultaneously every 15 minutes for 5 hours, during which time participants did not fast, feed and used their normal BGL protocol. A similar procedure was used for: stal, o.m., et al, (2018) Biosensors 8(4): 93.

Consider: (1) how participants were recruited, (2) whether our study was considered a clinical trial, and (3) whether ethical approval was required.

A summary of the potential devices to be used and the clinical trials/ethical considerations required is shown in figure 42. The middle dashed option is the option relevant at this stage. The left dotted option is possible, but it does not provide any further value to the study at this stage.

Example 11 additional development

Intention to

The non-invasive device of the present invention can be further developed, for example, to optimize the sensitivity and accuracy of the device and to study the use of wearable devices in more "real world" situations.

EIS instrument

Signal leakage

When the bioimpedance is measured using the electrodes of the device, the resulting stimulation signal shows a leakage path. Signal leakage does not affect the measurement quality. The generated stimulation signal is an important indicator that shows how much of the stimulation signal applied through the part of the body is being measured by the voltage sensing electrodes.

This can only be determined after ensuring that the internal electronics of the EIS instrument do not provide any leakage path, and that the signal leaks through a path on the body that is not detected by the voltage sensing electrodes of the wearable device. A possible effect surrounding this problem is that (i) inefficient electrode design results in a large fraction of the applied signal being unmeasured; (ii) there are potential equipment safety compliance issues if the applied signal level must be increased to overcome design inefficiencies.

Wearable ring

While ring-shaped designs using non-invasive wearable devices achieve acceptable performance of EIS instruments, optimization of sensitivity and accuracy can still be performed.

Electrode arrangement

Prior to human testing experiments, individual ring configurations were tested using EIS instruments.

Without being bound by any theory, the applicant believes that an ideal configuration would be a 4-terminal configuration, with the position of the voltage sensing electrode in the middle of the uniformly distributed current field. Figure 43 shows an alternative embodiment of the electrode configuration of the ring.

Electrode surface area

Electrodes with smaller surface areas can be developed. In one embodiment of the ring current configuration, a large capacitance is seen at low frequencies. Reducing the surface area of the voltage sensing electrode may solve this problem and may improve sensitivity.

Wearable watch

The traditional watch design of wearable devices differs from the bracelet in that the watch only measures the bio-impedance of one side of the wrist, whereas the bracelet measures the bio-impedance of a body part (i.e. the wrist). However, wearable watches may be developed to measure bio-impedance through a part of the body (such as the wrist).

Interference

External interference

During system testing, the effects of external electrical interference may occur, thereby affecting the quality of EIS instrumentation measurements. Faraday cages can be used to shield EIS instruments from these disturbances, resulting in high quality and repeatable measurements.

Although a faraday cage may be used to maintain signal quality in a controlled laboratory environment, it may not be practical for non-invasive equipment depending on the configuration. However, an optimized faraday cage can be developed to provide a non-invasive wearable device.

Internal interference

Another interference that affects the quality of the bio-impedance measurements is caused by movement of the subject to which the device is mounted.

Bioimpedance signal quality

Baseline reading and "intelligent" troubleshooting

The wearable device can detect the baseline reading and provide as basic troubleshooting as possible for the user. For example, an abnormally low bio-impedance measurement may mean that the electrodes are shorted by moisture or water on the skin. Conversely, an abnormally high bio-impedance may indicate poor electrode contact.

The non-invasive device of the present invention may be "intelligent" such that it can distinguish low quality measurements and provide an informative warning to the subject rather than providing an erroneous blood glucose concentration reading.

Pressure testing

All experiments in this study were highly controlled, and bioimpedance measurements were performed in consistent locations and conditions (e.g., participants lying down, limited motion, no electronics nearby, and wearable devices and EIS instruments in exactly the same location).

These highly controlled experiments are not representative of "real world" use of wearable devices. Wearable devices will be subject to constant motion, uncontrolled changes in homeostasis (e.g., hydration levels, perspiration), and external influences such as washing, application of creams (e.g., sunscreens, moisturizers), and hair growth.

Each of these effects must be explored to determine their effect on the bio-impedance measurement. With existing ring or bracelet wearable devices, for example, the effects of body posture (lying down, arm-in-the-air standing, arm-down standing), activity (before, during and after), and hydration (before, after drinking, bladder filling, bladder emptying) can be further studied.

Wearable position

The position of each electrode can be optimized. For example, in the example, ring embodiments were studied at only a single position on a single finger (L3) of each participant. Different orientations may be used as well as on different fingers.

A non-exhaustive list of some novel and/or inventive features of the present invention includes:

a) using bioimpedance to continuously and non-invasively measure blood glucose values on a finger;

b) continuously and non-invasively measuring blood glucose on a finger using bioimpedance in combination with other biometric information (including body temperature, pH, blood pressure);

c) continuously and non-invasively measuring blood glucose of a human body part using bio-impedance;

d) continuously and non-invasively measuring blood glucose of a human body part using bio-impedance in combination with other biometric information (including body temperature, pH, blood pressure);

e) using an Artificial Neural Network (ANN) model to correlate measured biometric information (including but not limited to bio-impedance, body temperature, pH, blood pressure) with blood glucose;

f) use different ANN architectures for different form factors (whether ring, bracelet, or other form);

g) using a dynamically adaptive ANN, this enables the ring to adapt to the user's specific biometric information pattern, thereby improving accuracy as the user continues to wear;

h) measuring bio-impedance using a wide frequency range of 0.1Hz to 1 MHz;

i) high quality signals were used to provide the ANN model: the measurement method may check the quality of the output current signal before use. Thus, filtering of noisy and low quality signals can be achieved, and only the high quality signals of the ANN can be used to improve the accuracy of the model or enable the functionality of the model;

j) positioning of the electrodes in the finger ring: existing devices place the electrodes on only one side of the body part (i.e. the wrist), whereas in our proposed device (i.e. the ring) the electrodes are placed in a configuration that allows current to pass through the body part, not just through the skin;

k) adjustable electrode contact mechanism to ensure reception of high quality signals while maintaining comfort: automatically adjusting the contact area of the electrode to ensure proper contact between the electrode and the skin to receive high quality signals;

l) adjustable electrode configuration to ensure reception of high quality signals. I.e., the locations of the current source and sink, the voltage sensing electrodes can be varied (not physically) on the PCB to ensure reception of a high quality signal; and

m) the electrodes may be mounted in a small fitting or in the form of a patch suitable for use in a mobile electronic device (e.g., mobile phone, iPad, iPod, etc.).

Example 12-alternative device configuration

Optimizing signal quality

Different parameters of the non-invasive device of the present invention can be adjusted to optimize the bio-impedance data according to the desired wearable device and configuration. The non-invasive device of the present invention preferably has the attributes of high signal quality, low data variability, and low bioimpedance amplitude, such that the apparatus can be sensitive to biological systems. The electrode design system may be sensitive to biological systems to identify changes in biological parameters, such as blood glucose levels.

Bio-impedance signal quality: the signal quality is assessed by measuring the noise and distortion levels of the bioimpedance signals. These parameters are evaluated based on the raw waveform output and the quality of discrete fourier transform fit (DFT QOF) output of the bio-impedance sensor.

Amplitude of bioimpedance: any electrode system can contribute significantly to the magnitude of the bio-impedance of the sample being analyzed. It is recommended to minimize this contribution to maximize the relative contribution of biological changes (e.g., changes in BGL). This results in a higher overall sensitivity. The amplitude of the bio-impedance was examined over the entire frequency range.

Repeatability: when measuring a single sample under stable conditions, it is desirable to ensure repeatability to minimize errors that may introduce bio-impedance measurements that would otherwise affect the feasibility of the predictive BGL model. Examining the variance in bioimpedance measurements provides a measure of repeatability when examining individual samples under stable conditions.

Electrode arrangement and spatial positioning

Non-invasive wearable devices in the form of four-electrode finger rings were evaluated to compare bio-impedance results generated with sensing electrodes placed on the same or opposite sides of the current path, as shown in fig. 44. The arrows indicate the passage of current through a portion of the body between the current injection electrodes. The remaining two electrodes are voltage measuring electrodes. The two current injection electrodes are configured to be substantially opposed, and the two voltage measurement electrodes are configured to be radially spaced relative to each current injection electrode by about greater than about 30 ° to about 60 ° and substantially opposed to each other. An example of a four-electrode ring device is shown in fig. 45a, and an exemplary non-invasive device is shown in fig. 45 b.

Bioimpedance data was recorded with an EIS instrument using 8 different configurations as shown in figure 44. These are intended to evaluate the position of the sensing electrode and the direction of the current flow. Representative bioimpedance results for the 8 different configurations are shown in fig. 44. The sense electrodes on opposite sides of the current path are configured in configurations 1-4 and the sense electrodes on the same side of the current path are configured in configurations 5-8. Higher variability and higher bioimpedance were observed with configurations 1-4, while lower variability and lower bioimpedance were observed with configurations 5-8. These configurations show the placement of the i-, i +, v-, and v + electrodes (i.e., fix the electrode locations, but change the electrodes to i-, i +, v-, and v +).

Lower bio-impedance was observed using sensing electrodes on the same side of the current path (configurations 5-8). The spatial location of these electrodes can be important because this location can determine how current flows through the user's finger when wearing the ring. The optimal spatial electrode position was determined by testing eight different current and voltage positions on the ring, as shown in figure 44. The locations are chosen because they are all possible permutations and combinations of current and voltage electrodes in a four electrode system. The location is estimated based on the magnitude of the bio-impedance and the quality of the generated waveform.

The four electrode device was then divided into 2 current injection electrodes (i-, i +) and 2 voltage measurement electrodes (v-, v +) (configuration 5-8).

The bio-impedance was then measured for one participant using an EIS machine. It has been consistently shown that current injection electrodes (i-and i +) on the same side and sensing electrodes (v-, v +) opposite the current electrodes produce consistent and reliable bioimpedance data (configurations 5-8). In three repetitions, the data has lower impedance amplitude, favorable waveform data, and "gold standard" type phase angle data. The inventors have surprisingly found that placing the current injection electrode and the voltage measurement electrode opposite each other (configurations 5-8) yields better signal quality; making the device more suitable for detecting changes in biological systems.

Another factor to consider is the spacing and/or spatial positioning between the electrodes. This is because the actual physical placement of the electrodes and the distance between them can determine which part of the finger is in contact with the finger ring. Preferably, the electrodes should be spaced far enough apart to reduce the risk of short circuits in the device, and also far enough to ensure a large flow path for current through the subject to maximize the amount of tissue on the bone.

This was tested by having the participants make bioimpedance measurements using an EIS machine with voltage measuring electrodes spaced 30 ° and 60 ° apart from the current injecting electrodes in a four electrode device, as shown in fig. 45. The path of the current through the finger is horizontal, i.e. a plane parallel to the plane of the palm.

FIG. 48 shows the effect of electrode spacing on the bio-impedance measurements. The 30 ° ring device has a higher impedance but less variation between repetitions than the 60 ° ring device. It was also observed that the signal amplitude of the 30 ° ring device was higher than the 60 ° ring device. The 60 ° ring device has a very low signal amplitude, resulting in a high variability of the bioimpedance measurements. The 30 ° ring device has a higher signal amplitude than the 60 ° ring device and also has a higher impedance, which reduces sensitivity to changes in biological impedance. Preferably a 30 deg. electrode spacing, finger ring device.

These relative angles are chosen because any smaller angle may increase the likelihood of a short circuit, and too far a distance may be uncomfortable. However, those skilled in the art will appreciate that angles less than 30 ° and angles greater than 60 ° may still be used with the present invention. The inventors have surprisingly found that electrodes spaced at an angle of 30 have better signal quality and lower impedance than electrodes spaced at an angle of 60. The 30 deg. embodiment also has a lower bio-impedance magnitude, which increases its sensitivity to bio-impedance changes.

It has also been found that if the ring device is held at an angle of 30, the likelihood of a short circuit increases if the size of the ring is reduced. The inventors have surprisingly found that a gap of 1mm between the two electrodes can provide greater flexibility in ring device design, as the gap can be used for all ring sizes. This allows the angle between the two electrodes to be varied while maintaining the proper distance between the electrodes as the ring size changes.

The calculations below can also show that the angle is kept between 24 and 33 for finger rings with dimensions 17-24mm (see below).

Theta is the angle between the electrodes

For ring size 17-24mm, θ (1.5mm × 360 °) 2 π r

r ═ (ring size)/2 π r

The angle between the two electrodes is thus 33-24.

Electrode shape

Different electrode shapes were used to compare the generated bio-impedance results. The electrodes are square or circular. Square shape (5X5mm diameter, 25 mm) was used with EIS instrument²) Or circular (5mm diameter, 19.63 mm)²Surface area) electrodes record bioimpedance data. Data were acquired sequentially in 3 positions and 3 repetitions of 1 participant. Two current path configurations (configurations 1 and 5) were tested.

Representative bioimpedance results for the square and circular electrodes are shown in fig. 46. The bio-impedance observed with the square electrodes is significantly lower. A typical "staircase" pattern was observed using square electrodes, indicating that the wearable device has a higher sensitivity to the finger layer.

The inventors have surprisingly found that square electrodes reliably reduce the amplitude of the impedance and produce much lower variability than circular electrodes. Applicants believe that this is the first time to show that square electrodes produce better results than round electrodes and that square electrodes can be more sensitive in detecting changes in biological parameters related to blood glucose levels.

Electrode size/surface area

Different electrode sizes/surface areas were used to compare the generated bioimpedance results. Bioimpedance data were recorded using configuration 5 using 2 different sizes of EIS instruments, in which the voltage measuring electrodes (5mm x5mm square electrodes "large", 2.5mm x 2.5mm "small" square electrodes) were adjusted between the two devices, but the current injection electrodes were the same size (5mm x5mm square electrodes). Data were acquired sequentially in 3 positions and 3 repetitions of 2 participants. Fig. 47 shows representative bio-impedance results using different sized electrodes.

As the skilled person will appreciate, the size and hence surface area of the electrodes comprising the voltage measuring electrodes will affect the contact area between the skin of the subject and the electrodes. This affects signal quality because a larger size increases the contact area with the skin, thereby increasing the electrical contact with the skin.

Although the large and small square electrodes indicate a good waveform, it was observed that the large voltage electrode reduced the amplitude of the bioimpedance and therefore increased the sensitivity of detecting changes in blood glucose levels. In one embodiment, large voltage measurement electrodes of 5mm by 5mm are preferred in the design of the ring because they have a higher sensitivity than smaller electrodes. The inventors believe that prior to the present invention, the specific dimensions of electrodes used to optimize bioimpedance measurements on non-invasive devices have not been determined.

Smaller electrodes (down to 1mm) contribute more to the magnitude of the bio-impedance. While increasing the size of the electrodes (up to 8mm or more) may further reduce the magnitude of the bio-impedance, this is balanced with the material cost and design constraints for fitting the ring. The inventors have surprisingly found that the best results are provided by current injection electrodes and voltage measurement electrodes having the same dimensions.

Finger ring position

Different positions of the ring device in use and different electrode configurations (configurations 1, 2, 5 and 6) were used to compare the resulting bioimpedance results. It was found that the horizontal current path on the finger always has a lower impedance magnitude than the vertical current path on the finger. Preferably horizontally. The horizontal current path is current flowing along a plane parallel to the plane of the palm and the vertical current path is in a plane perpendicular to the plane of the palm. Without being bound by any one theory, the inventors believe that when the ring is horizontal, the voltage and sensing electrodes interfere minimally with the signal from the bone because the outside of the finger has denser tissue. In contrast, when the ring is vertical, the electrical signal generated by the device must bypass more of the bone in the finger, resulting in a higher impedance. It was found that changing the position of the positive and negative current or voltage sensing electrodes had no effect on the magnitude of the impedance.

Finger ring tightness/contact pressure

The generated bioimpedance results are compared using different closeness of the ring device on the subject. Tightness, a measure of contact pressure, is important to ensure that the electrodes in the ring device are in sufficient contact with the subject's skin. Bioimpedance data was recorded using an EIS instrument from each of the 3 finger rings with 1mm size difference. The rings are either a tight fit (19mm), a measuring fit (20mm), or a loose fit (21 mm). These dimensions were chosen because they differed by ± 1mm from the measured diameter of the middle finger of the participant. Data were acquired sequentially in 3 positions and 3 repetitions of 1 participant. It was found that 19mm and 20mm finger rings showed typical variability in bioimpedance data after removal and replacement of the ring device, while loose 21mm ring devices showed significant variability.

In all measurements, a close fit to the ring produced consistent results (low impedance profile, good phase angle, reproducible signal quality). It was found that increasing the contact pressure does not result in a change in the quality of the generated bio-impedance data, but rather in a compromise in comfort. Poor quality bioimpedance measurements can be seen when the contact pressure is reduced and comfort is increased by a loose fitting finger ring.

The contact pressure should be tailored for each user to be comfortable enough to generate ideal bioimpedance data that is sensitive to biological systems.

The device/ring size kit may be used to achieve proper donning to match the participant's fingers to their most appropriate ring size.

Those skilled in the art will appreciate that the invention described herein is susceptible to variations and modifications other than those specifically described. It is to be understood that the invention includes all such variations and modifications which fall within the spirit and scope of the invention.