Minimally invasive multi-electrode bioelectrical impedance detection system and detection method
阅读说明：本技术 微创多电极生物电阻抗检测系统及检测方法 (Minimally invasive multi-electrode bioelectrical impedance detection system and detection method ) 是由 胡钦勇 燕自保 关欣 董朝阳 陈鹏飞 刘泉 于 2020-11-30 设计创作，主要内容包括：本发明提供一种微创多电极生物电阻抗检测系统及检测方法,它包括多个侵入式电极和检测系统,侵入式电极与检测系统电连接,检测系统用于对侵入式电极中的一个输出激励信号,并从其它侵入式电极中的一个或多个采集信号。检测系统的DDS信号源产生模拟正弦信号,通过低通滤波器和放大器经过基准校准和切换电路输出至其中一个侵入式电极,其他侵入式电极分别进行电流采样和/或电压采样。通过采用以上的结构,能够精确的测量得到皮肤、肌肉、积液以及血液等组织、器官的阻抗从而加以识别。(The invention provides a minimally invasive multi-electrode bioelectrical impedance detection system and a detection method, which comprise a plurality of invasive electrodes and a detection system, wherein the invasive electrodes are electrically connected with the detection system, and the detection system is used for outputting an excitation signal to one of the invasive electrodes and acquiring signals from one or more of other invasive electrodes. A DDS signal source of the detection system generates an analog sine signal, the analog sine signal is output to one of the invasive electrodes through a low-pass filter and an amplifier through a reference calibration and switching circuit, and the other invasive electrodes respectively perform current sampling and/or voltage sampling. By adopting the structure, the impedance of tissues and organs such as skin, muscle, effusion, blood and the like can be accurately measured and identified.)
1. A minimally invasive multi-electrode bioelectrical impedance detection system is characterized in that: it includes a plurality of invasive electrodes electrically connected to a detection system for outputting an excitation signal to one of the invasive electrodes and collecting signals from one or more of the other invasive electrodes.
2. The minimally invasive multi-electrode bioelectrical impedance detection system according to claim 1, characterized in that: the diameter of the invasive electrode is 0.05-0.35 mm, and the invasive electrode is used for penetrating human tissues.
3. The minimally invasive multi-electrode bioelectrical impedance detection system according to claim 1, characterized in that: the invasive electrode is provided with a plurality of micro needles arranged in an array, and the diameter of each micro needle is 0.05-0.35 mm;
the micro needles are fixedly connected with the base, and the base is connected with the shell in a sliding manner;
a drive device is arranged between the base and the housing for pushing out or withdrawing the microneedle from the housing.
4. The minimally invasive multi-electrode bioelectrical impedance detection system according to claim 1, characterized in that: the invasive electrode is 2 or more than 2 electrodes.
5. The minimally invasive multi-electrode bioelectrical impedance detection system according to claim 1, characterized in that: in the detection system, an output signal is electrically connected with the current detection module, and an input signal is electrically connected with the voltage detection module;
the current detection module and the voltage detection module are electrically connected with the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection and feedback compensation module is electrically connected with the reference calibration and switching circuit, and the reference calibration and switching circuit is electrically connected with the invasive electrode;
the calibration circuit is introduced into the tested end so as to obtain accurate data by at least two times of detection through switching;
the reference calibration and switching circuit is used for switching to different invasive electrodes to form various detection paths and acquire a bioelectrical impedance data matrix.
6. The minimally invasive multi-electrode bioelectrical impedance detection system according to claim 1, characterized in that: the main control device is electrically connected with a DDS signal source, the DDS signal source is electrically connected with a DAC module, the DAC module is electrically connected with an LPF low-pass filter, the LPF low-pass filter is electrically connected with an AMP amplifier, and the AMP amplifier is electrically connected with a current detection module;
the master control device is electrically connected with the ADC module, the ADC module is electrically connected with the LPF low-pass filter, the LPF low-pass filter is electrically connected with the TIA trans-impedance amplifier, and the TIA trans-impedance amplifier is electrically connected with the voltage detection module;
the current detection module and the voltage detection module are electrically connected with the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection and feedback compensation module is electrically connected with the reference calibration and switching circuit, and the reference calibration and switching circuit is electrically connected with the invasive electrode;
the reference calibration and switching circuit introduces a calibration circuit at the tested end to obtain accurate data by at least two times of detection through switch switching.
7. The minimally invasive multi-electrode bioelectrical impedance detection system according to any one of claims 5 and 6, characterized in that: in the AMP amplifier, an INHI pin of a chip AD8369 is electrically connected with one end of a first capacitor (C1), an INLO pin of the chip AD8369 is electrically connected with one end of a second capacitor (C2), and the other ends of the first capacitor (C1) and the second capacitor (C2) are electrically connected through a first resistor (R1);
an OPHI pin of the chip AD8369 is electrically connected with one end of a third capacitor (C3), the other end of the third capacitor (C3) is electrically connected with a 3 rd pin of the chip AD8009 through an RC parallel circuit, and a fourth resistor (R4) is connected between the third capacitor (C3) and the RC parallel circuit and the 1 st pin of the chip AD 8009;
the OPLO pin of the chip AD8369 is electrically connected with one end of a fourth capacitor (C4), the other end of the fourth capacitor (C4) is electrically connected with the 2 nd pin of the chip AD8009 through an RC parallel circuit, and the fourth capacitor (C4) and the RC parallel circuit are grounded;
a 5 th resistor (R5) is connected between the 1 st pin and the 2 nd pin of the chip AD8009, and a 6 th resistor (R6) is connected between the 1 st pin and the 3 rd pin of the chip AD 8009;
the chip AD8009 is used for converting the output differential signal into a single-ended signal, and the chip AD8369 is used for digital controllable gain amplification.
8. The minimally invasive multi-electrode bioelectrical impedance detection system according to any one of claims 5 and 6, characterized in that: in the reference calibration and switching circuit, the reference calibration circuit and the detection circuit are switched by a circuit switching module to eliminate noise interference and channel contact impedance;
the reference calibration and switching circuit is provided with a plurality of 1-to-N switches (N is more than 2) so that a signal source is received by a plurality of invasive electrodes and a plurality of receiving ends in the detection module, and a bioelectrical impedance data matrix is acquired in a real-time manner; each invasive electrode is alternately and electrically connected with a signal source;
or the reference calibration and switching circuit is provided with a plurality of switches of 1 to 2, so that a signal source is received by 1 invasive electrode and is received by 1 receiving terminal in the detection module, and a bioelectrical impedance data matrix is acquired in a time-sharing multiplexing mode; each invasive electrode is alternately and electrically connected with a signal source.
9. The minimally invasive multi-electrode bioelectrical impedance detection system according to any one of claims 5 and 6, characterized in that: and (5) a plurality of groups of operational amplifier chips are arranged in the TIA trans-impedance amplifier, and the operational amplifier chips are used for converting current signals into voltage signals.
10. The minimally invasive multi-electrode bioelectrical impedance detection system according to any one of claims 5 and 6, characterized in that: in the digital phase-sensitive detection and feedback compensation module, a chip AD8302 is adopted as a gain phase detector in the digital phase-sensitive detection part, and the impedance amplitude and the phase of the load to be detected are calculated by comparing the amplitude and the phase between the known load and the load to be detected.
11. The minimally invasive multi-electrode bioelectrical impedance detection system according to any one of claims 5 and 6, characterized in that: in the digital phase-sensitive detection and feedback compensation module, a feedback compensation part is provided with a digital adjustable resistor and a variable capacitor to form an electrical impedance model of the internal tissues of the human body, and the electrical impedance model is used as a compensation circuit of the tissues to be detected.
12. The minimally invasive multi-electrode bioelectrical impedance detection system according to any one of claims 11, wherein: the PWM signal-to-analog signal converter is also arranged and is used for generating controllable voltage through linear constant voltage and constant current driving so as to adjust the variable capacitor.
13. A detection method using the minimally invasive multi-electrode bioelectrical impedance detection system of any one of claims 1 to 12, characterized by comprising the steps of: a DDS signal source of the detection system generates an analog sine signal, the analog sine signal is output to one of the invasive electrodes through a low-pass filter and an amplifier through a reference calibration and switching circuit, and the other invasive electrodes respectively perform current sampling and/or voltage sampling.
14. A detection method using the minimally invasive multi-electrode bioelectrical impedance detection system of any one of claims 1 to 13, characterized by comprising the steps of:
s1, detecting target tissues of different individuals, switching to different invasive electrodes to form various detection paths, acquiring a bioelectrical impedance data matrix to form a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissues;
and S2, obtaining detection results by comparing the radio frequency images of the target tissues of different individuals.
15. A detection method using the minimally invasive multi-electrode bioelectrical impedance detection system of any one of claims 1 to 13, characterized by comprising the steps of:
s1, detecting the target tissue of the same individual at different time periods, forming various detection paths by switching to different invasive electrodes, acquiring a bioelectrical impedance data matrix, forming a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissue;
and S2, obtaining detection results by comparing the radio frequency images of the target tissues at different time periods.
16. A detection method using the minimally invasive multi-electrode bioelectrical impedance detection system of any one of claims 1 to 13, characterized by comprising the steps of:
s1, detecting target tissues of different individuals, switching to different invasive electrodes to form various detection paths, acquiring a bioelectrical impedance data matrix to form a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissues;
detecting target tissues of the same individual at different time periods to form a multi-frequency matrix type scanning image and construct radio frequency image data of the target tissues;
s2, constructing the radio frequency image data of the target tissue in the normal state by obtaining the radio frequency image data, and comparing the currently detected radio frequency image data with the radio frequency image data of the target tissue in the normal state to obtain a detection result.
17. A detection method using the minimally invasive multi-electrode bioelectrical impedance detection system according to any one of claims 14 to 16, characterized by comprising the steps of:
an artificial intelligence recognition model is also arranged;
the artificial intelligence recognition model is trained by using input radio frequency image data to obtain the artificial intelligence recognition model for recognizing human tissues according to the radio frequency image data acquired by the invasive electrode.
Technical Field
The invention relates to the field of medical instruments, in particular to a minimally invasive multi-electrode bioelectrical impedance detection system.
Background
The traditional Bioelectrical Impedance Analysis (BIA) is an indirect method for evaluating body components, and the basic idea is to simplify the human body into different models and then to introduce weak alternating current signals into the human body, so that the current flows along body fluid with small resistance and good conductivity. Through a large amount of test data, the statistical relationship existing between the electrical impedance characteristics of the human body and the body composition is established, and the body composition measurement principle is based on the bioelectrical impedance technology. With the development of electronic technology, researchers have further proposed a body composition measurement method based on Bioelectrical Impedance Spectroscopy (BIS), which selects multiple frequency points within a frequency range, calculates characteristic parameters of a human body by using the measured impedance values according to a model of human body impedance, and further calculates human body compositions, and the accuracy of the calculation depends on the establishment of a human body composition model.
Medical research shows that when diseases occur, functional changes of related tissues and organs are prior to organic diseases, structural changes of the tissues and the organs or other clinical symptoms occur after a certain latency period, and the results can be diagnosed only when the structural changes of pathological tissues are achieved by traditional CT, MRI, ultrasound and other detection technologies, so that the disease course of a patient is developed to the middle and later stages when the patient is examined in a hospital, and the treatment time is delayed. At present, bioelectrical impedance tomography (EIT) based on BIA technology is also dedicated to the application and research in the aspect, the EIT uses a non-invasive mode to detect the short-term change of the physiological state of biological tissues, and has important clinical value and application prospect in the aspects of researching the physiological function of human bodies and diagnosing diseases. However, in the medical field, detection and treatment of local complex physiological and pathological tissues of a human body, such as local detection and positioning of muscle tissues, adipose tissues, blood, tumors or pathological tissues, etc., at this time, the EIT non-invasive detection technology has technical limitations in weak signal detection, large dynamic range detection, noise immunity, reconstruction algorithm, etc., resulting in large tolerance of a measurement sample, insufficient local sensitivity and precision, uncontrollable detection time, etc.
Chinese patent document CN 111787849 a describes a method for predicting recurrence of cancer cells in a patient, the method comprising: measuring a first impedance of a first slice of a first tissue sample excised from the patient by including a first subset of electrodes in an electrode array operating at a first frequency; calculating a first Kerr (Cole) relaxation frequency of the first slice of the first sample based on the first impedance; and generating a first prediction related to the patient cancer cells based at least in part on the first coul relaxation frequency. However, this solution is used to measure tissue slices of a patient, is highly harmful to the patient and is difficult to use as a preventive measure.
Disclosure of Invention
The invention aims to provide a minimally invasive multi-electrode bioelectrical impedance detection system which can quickly, accurately and accurately detect and identify human tissues in the coverage range of invasive electrodes and position skin, muscles, body fluid and blood.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a minimally invasive multi-electrode bioelectrical impedance sensing system includes a plurality of invasive electrodes electrically connected to a sensing system for outputting an excitation signal to one of the invasive electrodes and collecting signals from one or more of the other invasive electrodes.
In a preferable scheme, the diameter of the invasive electrode is 0.05-0.35 mm, and the invasive electrode is used for penetrating human tissues.
In a preferable scheme, the invasive electrode is provided with a plurality of micro needles arranged in an array, and the diameter of each micro needle is 0.05-0.35 mm;
the micro needles are fixedly connected with the base, and the base is connected with the shell in a sliding manner;
a drive device is arranged between the base and the housing for pushing out or withdrawing the microneedle from the housing.
In a preferred embodiment, the invasive electrode is 2 or more than 2 electrodes.
In a preferred scheme, in the detection system, an output signal is electrically connected with the current detection module, an input signal is electrically connected with the voltage detection module,
the current detection module and the voltage detection module are electrically connected with the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection and feedback compensation module is electrically connected with the reference calibration and switching circuit, and the reference calibration and switching circuit is electrically connected with the invasive electrode;
the calibration circuit is introduced into the tested end so as to obtain accurate data by at least two times of detection through switching;
the reference calibration and switching circuit is used for switching to different invasive electrodes to form various detection paths and collecting a bioelectrical impedance data matrix.
In a preferred scheme, the main control device is electrically connected with a DDS signal source, the DDS signal source is electrically connected with a DAC module, the DAC module is electrically connected with an LPF low-pass filter, the LPF low-pass filter is electrically connected with an AMP amplifier, and the AMP amplifier is electrically connected with a current detection module;
the master control device is electrically connected with the ADC module, the ADC module is electrically connected with the LPF low-pass filter, the LPF low-pass filter is electrically connected with the TIA trans-impedance amplifier, and the TIA trans-impedance amplifier is electrically connected with the voltage detection module;
the current detection module and the voltage detection module are electrically connected with the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection and feedback compensation module is electrically connected with the reference calibration and switching circuit, and the reference calibration and switching circuit is electrically connected with the invasive electrode;
the reference calibration and switching circuit introduces a calibration circuit at the tested end to obtain accurate data by at least two times of detection through switch switching.
In a preferred scheme, in the AMP amplifier, an INHI pin of a chip AD8369 is electrically connected to one end of a first capacitor (C1), an INLO pin of the chip AD8369 is electrically connected to one end of a second capacitor (C2), and the other ends of the first capacitor (C1) and the second capacitor (C2) are electrically connected through a first resistor (R1);
an OPHI pin of the chip AD8369 is electrically connected with one end of a third capacitor (C3), the other end of the third capacitor (C3) is electrically connected with a 3 rd pin of the chip AD8009 through an RC parallel circuit, and a fourth resistor (R4) is connected between the third capacitor (C3) and the RC parallel circuit and the 1 st pin of the chip AD 8009;
the OPLO pin of the chip AD8369 is electrically connected with one end of a fourth capacitor (C4), the other end of the fourth capacitor (C4) is electrically connected with the 2 nd pin of the chip AD8009 through an RC parallel circuit, and the fourth capacitor (C4) and the RC parallel circuit are grounded;
a 5 th resistor (R5) is connected between the 1 st pin and the 2 nd pin of the chip AD8009, and a 6 th resistor (R6) is connected between the 1 st pin and the 3 rd pin of the chip AD 8009;
the chip AD8009 is used for converting the output differential signal into a single-ended signal, and the chip AD8369 is used for digital controllable gain amplification.
In a preferred scheme, in the reference calibration and switching circuit, a circuit switching module is used for switching between a reference calibration circuit and a detection circuit so as to eliminate noise interference and channel contact impedance;
the reference calibration and switching circuit is provided with a plurality of 1-to-N switches (N is more than 2) so that a signal source is received by a plurality of invasive electrodes and a plurality of receiving ends in the detection module, and a bioelectrical impedance data matrix is acquired in a real-time manner; each invasive electrode is alternately and electrically connected with a signal source;
or the reference calibration and switching circuit is provided with a plurality of switches of 1 to 2, so that a signal source is received by 1 invasive electrode and is received by 1 receiving terminal in the detection module, and a bioelectrical impedance data matrix is acquired in a time-sharing multiplexing mode; each invasive electrode is alternately and electrically connected with a signal source.
In a preferred scheme, a plurality of sets of operational amplifier chips are arranged in the TIA transimpedance amplifier, and the operational amplifier chips are used for converting current signals into voltage signals.
In a preferred scheme, in the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection part adopts a chip AD8302 as a gain phase detector, and the impedance amplitude and phase of the load to be detected are calculated by comparing the amplitude and phase between the known load and the load to be detected.
In the preferred scheme, in the digital phase-sensitive detection and feedback compensation module, a feedback compensation part is provided with a digital adjustable resistor and a variable capacitor to form an electrical impedance model of the internal tissues of the human body, and the electrical impedance model is used as a compensation circuit of the tissues to be detected.
In a preferred scheme, a PWM signal-to-analog signal converter is further arranged, and controllable voltage is generated through linear constant voltage and constant current driving and is used for adjusting the variable capacitor.
A detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps: a DDS signal source of the detection system generates an analog sine signal, the analog sine signal is output to one of the invasive electrodes through a low-pass filter and an amplifier through a reference calibration and switching circuit, and the other invasive electrodes respectively perform current sampling and/or voltage sampling.
A detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
s1, detecting target tissues of different individuals, switching to different invasive electrodes to form various detection paths, acquiring a bioelectrical impedance data matrix to form a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissues;
and S2, obtaining detection results by comparing the radio frequency images of the target tissues of different individuals.
A detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
s1, detecting the target tissue of the same individual at different time periods, forming various detection paths by switching to different invasive electrodes, acquiring a bioelectrical impedance data matrix, forming a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissue;
and S2, obtaining detection results by comparing the radio frequency images of the target tissues at different time periods.
A detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
s1, detecting target tissues of different individuals, switching to different invasive electrodes to form various detection paths, acquiring a bioelectrical impedance data matrix to form a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissues;
detecting target tissues of the same individual at different time periods to form a multi-frequency matrix type scanning image and radio frequency image data of the target tissues;
s2, constructing the radio frequency image data of the target tissue in the normal state by obtaining the radio frequency image data, and comparing the currently detected radio frequency image data with the radio frequency image data of the target tissue in the normal state to obtain a detection result.
A detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
an artificial intelligence recognition model is also arranged;
the artificial intelligence recognition model is trained by using input radio frequency image data to obtain the artificial intelligence recognition model for recognizing human tissues according to the radio frequency image data acquired by the invasive electrode.
The invention provides a minimally invasive multi-electrode bioelectrical impedance detection system and a detection method, which can accurately measure and obtain the impedance of tissues and organs such as skin, muscle, effusion, blood and the like by adopting the structure so as to identify the impedance. Furthermore, the abnormal impedance state of the tumor or the pathological tissue can be screened or prompted in advance. Compared with the prior art, the high-resistance anti-interference of the skin is avoided, and the measurement precision of the invasive electrode is 100,000-1,000,000 times of that of the bioelectrical impedance analysis method in the prior art. By adopting the artificial intelligence model, the detection and identification efficiency can be greatly improved, the detection and identification precision can be improved, and especially, the tissue lesion can be warned in the early stage. The invention can greatly improve the detection precision by means of multi-frequency imaging, radio frequency imaging and the like. A high-precision ammeter, a precision differential voltmeter and a trans-impedance amplifier are arranged in the detection system to realize weak signal detection. And a multistage second-order active filter is arranged, so that the signal-to-noise ratio is improved. The detection precision is further improved by arranging a digital phase-sensitive detection, namely a feedback compensation module. The set reference calibration and switching circuit module drives and detects adjacent electrodes, and interference can be reduced. And a secondary detection compensation algorithm and an artificial intelligence algorithm are also arranged in the master control system, so that the data processing efficiency is further improved.
Drawings
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
FIG. 1 is a schematic structural diagram of the present invention.
Fig. 2 is a block diagram of the system of the present invention.
FIG. 3 is a diagram of a standard calibration circuit according to the present invention.
FIG. 4 is a diagram of an AMP amplifying circuit according to the present invention.
FIG. 5 is a diagram of a reference calibration circuit and a detection circuit according to the present invention.
Fig. 6 is a circuit diagram of a TIA transimpedance amplifier according to the present invention.
FIG. 7 is a diagram of the digital phase-sensitive detection scheme of the present invention.
FIG. 8 is a circuit diagram of an amplitude and phase detector according to the present invention.
FIG. 9 is a diagram of a compensation circuit according to the present invention.
FIG. 10 is a schematic view of the four-electrode measurement according to the present invention.
FIG. 11 is a schematic diagram illustrating the determination of the four-electrode measurement result according to the present invention.
FIG. 12 is a schematic diagram of a 1-to-N switch array according to the present invention.
FIG. 13 is a schematic diagram of a 2-from-1 switch array according to the present invention.
FIG. 14 is a model of a local tissue of a human body in the absence of an excitation signal according to the present invention.
FIG. 15 is a model of a local tissue of a human body under excitation signals in accordance with the present invention.
Fig. 16 is a schematic view of the structure of the invasive electrode of the present invention.
FIG. 17 is a graph of the skin frequency response of the present invention.
Fig. 18 is a graph of fat frequency response in the present invention.
Figure 19 is a graph of the frequency response of muscles according to the invention.
FIG. 20 is a graph of the frequency response of blood in accordance with the present invention.
FIG. 21 is a graph showing the real part versus the imaginary part of the microscopic change in blood in the present invention.
Detailed Description
Example 1:
as shown in fig. 1-2, the minimally invasive multi-electrode bioelectrical impedance detection system comprises a plurality of invasive electrodes and a detection system, wherein the invasive electrodes are electrically connected with the detection system, and the detection system is used for outputting an excitation signal to one of the invasive electrodes and collecting signals from one or more of other invasive electrodes. With this structure, high-precision human body impedance data can be obtained.
The preferred scheme is as shown in figure 16, the diameter of the invasive electrode is 0.05-0.35 mm, and the invasive electrode is used for penetrating human tissues. For example, the skin of a human body, so as to avoid the skin from interfering with the electrical signals. Further preferably, the electrode has a sufficient length, and can penetrate into a human body to further assist in detection of a target organ. For example, auxiliary detection of positions of lung, liver, kidney, etc.
The preferable scheme is as shown in figure 16, the invasive electrode is provided with a plurality of micro needles arranged in an array, and the diameter of each micro needle is 0.05-0.35 mm;
the micro needles are fixedly connected with the base, and the base is connected with the shell in a sliding manner;
a drive device is arranged between the base and the housing for pushing out or withdrawing the microneedle from the housing. The driving device comprises a cam mechanism, a crank rocker mechanism, a gear rack mechanism or a lead screw nut mechanism which are driven by a stepping motor, and drives the micro needle to be pushed out of or retracted from the shell. The travel of the micro needle is controlled by controlling the rotation angle of the stepping motor.
The preferable scheme is as shown in fig. 16, the invasive electrodes are 2-8 electrodes; preferably, 2, 4 and 8 electrodes.
Alternatively, the invasive electrodes are more than 8 electrodes arranged in an array, for example 12, 16 or 32 electrodes. Further preferably, the invasive electrode is a silver-plated electrode. Because the diameter of the electrode is smaller, the detected person is hardly damaged in the using process.
In a preferred embodiment, as shown in fig. 1 and 2, in the detection system, the output signal is electrically connected to the current detection module, the input signal is electrically connected to the voltage detection module,
the current detection module and the voltage detection module are electrically connected with the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection and feedback compensation module is electrically connected with the reference calibration and switching circuit, and the reference calibration and switching circuit is electrically connected with the invasive electrode;
the calibration circuit is introduced into the tested end so as to obtain accurate data by at least two times of detection through switching;
the reference calibration and switching circuit is used for switching to different invasive electrodes to form various detection paths and collecting a bioelectrical impedance data matrix. A DDS signal source of the detection system generates an analog sine signal, the analog sine signal is output to one of the invasive electrodes through a low-pass filter and an amplifier through a reference calibration and switching circuit, and the other invasive electrodes respectively perform current sampling and/or voltage sampling. It is further preferable that the adjacent electrode driving detection mode is adopted, that is, one adjacent electrode injects exciting current to the field area, a sensitive field is established, and boundary voltage is measured on other adjacent electrodes. Then switching to the next adjacent electrode pair for excitation, measuring the voltage on other adjacent and non-excited electrode pairs, and repeating the process until all adjacent electrode pairs are excited, so that the scheme can obtain the reticular sensitive radio frequency detection data.
In a preferred scheme, as shown in fig. 1 and 2, the main control device is electrically connected with a DDS signal source, the DDS signal source is electrically connected with a DAC module, the DAC module is electrically connected with an LPF low-pass filter, the LPF low-pass filter is electrically connected with an AMP amplifier, and the AMP amplifier is electrically connected with a current detection module;
the master control device is electrically connected with the ADC module, the ADC module is electrically connected with the LPF low-pass filter, the LPF low-pass filter is electrically connected with the TIA trans-impedance amplifier, and the TIA trans-impedance amplifier is electrically connected with the voltage detection module;
the current detection module and the voltage detection module are electrically connected with the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection and feedback compensation module is electrically connected with the reference calibration and switching circuit, and the reference calibration and switching circuit is electrically connected with the invasive electrode;
as shown in fig. 3 and 5, the reference calibration and switching circuit introduces a calibration circuit at the tested end to switch through a switch to obtain accurate data by at least two tests. With the circuit configuration, highly accurate detection data is obtained.
In a preferred scheme, as shown in fig. 4, in the AMP amplifier, an INHI pin of a chip AD8369 is electrically connected to one end of a first capacitor (C1), an INLO pin of the chip AD8369 is electrically connected to one end of a second capacitor (C2), and the other ends of the first capacitor (C1) and the second capacitor (C2) are electrically connected through a first resistor (R1);
an OPHI pin of the chip AD8369 is electrically connected with one end of a third capacitor (C3), the other end of the third capacitor (C3) is electrically connected with a 3 rd pin of the chip AD8009 through an RC parallel circuit, and a fourth resistor (R4) is connected between the third capacitor (C3) and the RC parallel circuit and the 1 st pin of the chip AD 8009;
the OPLO pin of the chip AD8369 is electrically connected with one end of a fourth capacitor (C4), the other end of the fourth capacitor (C4) is electrically connected with the 2 nd pin of the chip AD8009 through an RC parallel circuit, and the fourth capacitor (C4) and the RC parallel circuit are grounded;
a 5 th resistor (R5) is connected between the 1 st pin and the 2 nd pin of the chip AD8009, and a 6 th resistor (R6) is connected between the 1 st pin and the 3 rd pin of the chip AD 8009;
the chip AD8009 is used for converting the output differential signal into a single-ended signal, and the chip AD8369 is used for digital controllable gain amplification.
In the preferred embodiment as shown in fig. 3 and 5, in the reference calibration and switching circuit, the reference calibration circuit and the detection circuit are switched by the circuit switching module to eliminate noise interference and channel contact impedance;
further preferably, as shown in fig. 12, the reference calibration and switching circuit is provided with a plurality of switches (N > 2) selected by 1 from N, so that a signal source is received by a plurality of invasive electrodes and received by a plurality of receiving terminals in the detection module, and a bioelectrical impedance data matrix is acquired in a real-time manner; each invasive electrode is alternately and electrically connected with a signal source; the switching speed of the switch matrix is us grade, and if N1-to-N switches are used, the switching times are N times.
Or, as another alternative, as shown in fig. 13, the reference calibration and switching circuit is provided with a plurality of switches from 1 to 2, so that one signal source is received by 1 invasive electrode, and is received by 1 receiving terminal in the detection module, and the bioelectrical impedance data matrix is acquired in a time-division multiplexing manner; each invasive electrode is alternately and electrically connected with a signal source. Considering that the pathological change time of human tissue is not instantaneous, in order to reduce the number of switch matrixes and the circuit complexity, N1-to-2 switches can be adopted, and the switching frequency is N2And/2, under the condition that the excitation source is not changed, the receiving end circuit adopts a time division multiplexing scheme.
In a preferred scheme, as shown in fig. 6, a plurality of sets of operational amplifier chips are arranged in the TIA transimpedance amplifier, and the operational amplifier chips are configured to convert a current signal into a voltage signal.
In the preferred scheme, as shown in fig. 7 and 8, in the digital phase-sensitive detection and feedback compensation module, the digital phase-sensitive detection part adopts a chip AD8302 as a gain phase detector, and calculates the impedance amplitude and phase of the load to be measured by comparing the amplitude and phase between the known load and the load to be measured.
In the preferred scheme, as shown in fig. 9, in the digital phase-sensitive detection and feedback compensation module, a feedback compensation part is provided with a digital adjustable resistor and a variable capacitor to form an electrical impedance model of the internal tissue of the human body, which is used as a compensation circuit of the detected tissue.
In a preferred scheme, a PWM signal-to-analog signal converter is further arranged, and controllable voltage is generated through linear constant voltage and constant current driving and is used for adjusting the variable capacitor.
The invention adopts an ADC circuit with 16-bit precision, the effective data bit reaches more than 13 bits under the frequency of 300K, the actual measurement precision of the biological tissue can reach the milliohm level, and the resolution of the detection result is greatly improved. By adopting the scheme of the embodiment 1, the fact that the electrical impedance frequency spectrum of the cancerated tissue has larger difference with the normal tissue in the curvature change can be used as a basis for judging the normal human tissue and canceration. Therefore, the scheme of the embodiment 1 can realize early-stage pathological early warning. In the prior art, tissue canceration occurs in a very early stage, and no good detection means such as breast cancer exists, and the tissue canceration can be basically found in a middle and late stage. The scheme of the invention has a wide application prospect in the field of mammary gland detection.
Example 2:
on the basis of embodiment 1, as shown in fig. 10 and 11, a detection method using the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps: a DDS signal source of the detection system generates an analog sine signal, the analog sine signal is output to one of the invasive electrodes through a low-pass filter and an amplifier through a reference calibration and switching circuit, and the other invasive electrodes respectively perform current sampling and/or voltage sampling.
Referring to fig. 10 and 11, using bipolar impedance measurements, a multi-invasive electrode distribution is used on a human body, e.g., head, chest, abdomen, arm, etc., and different paths are constructed by switching the switch matrix at the front end of the electrodes when the number of electrodes is N (N > 2). For example, in FIG. 7, the sequence 1 electrode is used as the excitation source, and the next N-1 electrodes are used as the measurement electrodes; taking the sequence 2 electrode as an excitation source, and taking the back N-2 electrodes as measuring electrodes; the data of N x (N-1)/2 groups can be obtained in sequence, and the position of the abnormal tissue in the body can be positioned by utilizing the mutual relation among the data.
As shown in fig. 10, taking N-4 as an example, when the electrode 1 is an excitation source, the electrodes 2, 3, and 4 are measurement electrodes, and the impedance between 1 and 2, the impedance between 1 and 3, and the impedance between 1 and 4 are obtained; switching a switch matrix, using the electrode 2 as an excitation source, and using the electrodes 3 and 4 as measuring electrodes, and measuring the impedance between the electrodes 2 and 3 and the impedance between the electrodes 2 and 4; finally, switching 3 to be an excitation source and 4 to be a measuring electrode, and measuring the impedance between 3 and 4.
The impedance between the 4 electrodes is expressed as follows:
whereinMijBeing the amplitude of the impedance,. omega.tauijIs the phase of the impedance.
By the support of big data, the invasive electrode of the invention can detect and identify different human tissues in real time, further can detect the changes of pathological tissues and the like in human organs in real time, and has 4 electrode impedance matrix change rates
And obtaining the closed area according to the relative position information between the 4 electrodes. In FIG. 11, Δ Z is the maximum rate of change12， △Z13The second major rate of change between the electrode areas 1, 2 and 3 is Δ Z14And Δ Z24And judging that the superposition position of the two regions is the tissue lesion position among the electrode regions 1, 2 and 4.
It can be seen from this that, as the number of invasive electrodes is increased, the narrower the area range is, the more accurate the position information can be determined, and certainly, as the number of electrodes is not increased, the better the position information is, and as the number of electrodes is increased, the resolution of the voltage signal is also improved, and at the same time, the calculation amount of the processor is increased in a geometric scale, so the number of electrodes should be selected according to the size of the measurement area.
Example 3:
on the basis of the embodiment, the detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
s1, detecting target tissues of different individuals, switching to different invasive electrodes to form various detection paths, acquiring a bioelectrical impedance data matrix to form a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissues;
and S2, obtaining detection results by comparing the radio frequency images of the target tissues of different individuals. As shown in fig. 17-21, it can be seen that the radio frequency images obtained from different tissues have obvious differences, so that different target tissues can be distinguished. As in fig. 21, human tissue classification: epithelial tissue, connective tissue, muscle tissue, nerve tissue; main components of the human body: water, sugar, fat, protein, inorganic salt. The cell membrane electrical model shows that the cell membrane is composed of a lipid bilayer, the interior of the lipid bilayer is filled with a dielectric medium, and the outer side and the inner side of the membrane are respectively filled with extracellular fluid and intracellular fluid, which are regarded as conductor solutions. Therefore, the cell membrane formed by the lipid bilayer is equivalent to a capacitor in electrical property, the lipid bilayer is two polar plates of the capacitor, the two polar plates are respectively connected with the fluid in the conductor extracellular fluid cell, and the middle of the two polar plates is filled with a dielectric medium. The structure of the cell membrane is not only a lipid bilayer, but also proteins embedded therein, some of which are so-called "ion channels", and their presence allows transport of ions across the membrane, i.e. the cell membrane is a "leaky capacitor", which allows current to pass through the dielectric between the plates, the leaky capacitor being represented by an ideal capacitor in parallel with a resistor. This is an electrical model of the cell membrane as shown in figure 15. Therefore, in the case of abnormal tissue, such as inflammation, when the increase of cells occurs, the density becomes higher, or the volume of cells becomes larger, the resistance-capacitance parameter is more or less changed within a certain volume range, so that the abnormal tissue can be identified by the corresponding data, and in the scheme of the present application, the skin interference as shown in fig. 14 is eliminated, so that the identification precision can be greatly improved. Blood consists of plasma and blood cells, the liquid between the blood cells can be regarded as electrolyte, and the constitution of the blood determines that the blood shows resistance-capacitance-resistance characteristics under the action of an alternating electric field. The detection of the blood frequency spectrum characteristic extracts rich resistance-capacitance resistance complete information related to human physiological and pathological states from the cellular level, and plays a positive auxiliary role in clinical analysis and prevention.
Example 4:
on the basis of the embodiment, the detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
s1, detecting the target tissue of the same individual at different time periods, forming various detection paths by switching to different invasive electrodes, acquiring a bioelectrical impedance data matrix, forming a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissue;
and S2, obtaining detection results by comparing the radio frequency images of the target tissues at different time periods. According to the scheme, if the target tissue of the same individual, such as mammary gland tissue, is detected once every half year, when the difference exceeding the threshold value occurs, the individual can be warned to take other more detections, so as to control the risk within a very small range.
Example 5:
on the basis of the embodiment, the detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
s1, detecting target tissues of different individuals, switching to different invasive electrodes to form various detection paths, acquiring a bioelectrical impedance data matrix to form a multi-frequency matrix type scanning image, and constructing radio frequency image data of the target tissues;
detecting target tissues of the same individual at different time periods to form a multi-frequency matrix type scanning image and radio frequency image data of the target tissues;
s2, constructing the radio frequency image data of the target tissue in the normal state by obtaining the radio frequency image data, and comparing the currently detected radio frequency image data with the radio frequency image data of the target tissue in the normal state to obtain a detection result. By establishing a big data model, taking mammary gland as an example, the characteristic points of normal tissues and specific tissues, such as different impedance curvature morphological changes, are found out. Thereby greatly reducing the difficulty of identification.
Example 6:
on the basis of the embodiment, the detection method adopting the minimally invasive multi-electrode bioelectrical impedance detection system comprises the following steps:
an artificial intelligence recognition model is also arranged;
alternative artificial intelligence tools include CNN, Faster R-CNN, VGG16, and the like.
The artificial intelligence recognition model is trained by using input radio frequency image data to obtain the artificial intelligence recognition model for recognizing human tissues according to the radio frequency image data acquired by the invasive electrode. By acquiring a large number of biological resistance spectrum images and corresponding the images to the pathological information diagnosed by the acquired person. When the data volume reaches a certain scale, the images can be associated with the corresponding tissue diagnosis characteristics. The data are used for training the artificial intelligent recognition model, so that the recognition accuracy and efficiency can be greatly improved in the processing process.
The above-described embodiments are merely preferred embodiments of the present invention, and should not be construed as limiting the present invention, and features in the embodiments and examples in the present application may be arbitrarily combined with each other without conflict. The protection scope of the present invention is defined by the claims, and includes equivalents of technical features of the claims. I.e., equivalent alterations and modifications within the scope hereof, are also intended to be within the scope of the invention.