阅读说明：本技术 睡眠改善方法和智能床垫 (Sleep improvement method and intelligent mattress ) 是由 王炳坤 于 2021-09-29 设计创作，主要内容包括：本发明公开了一种睡眠改善方法和智能床垫。该睡眠改善方法应用于智能床垫,智能床垫包括床垫本体、点阵式传感器阵列和处理器,床垫本体包括气囊组件,点阵式传感器阵列和处理器电连接；点阵式传感器阵列设置在床垫本体上；点阵式传感器阵列用于感知人体体征信息以得到传感器点值图；睡眠改善方法包括：获取传感器点值图；基于传感器点值图确定当前支撑信息,当前支撑信息包括支撑面积信息和支撑力度信息；基于当前支撑信息确定目标支撑信息,目标支撑信息包括目标支撑面积信息和目标支撑力度信息；基于目标支撑信息调节气囊组件的气体量。通过采用上述方案,实现了提高智能调节的精准度以改善使用者睡眠的效果。(The invention discloses a sleep improvement method and an intelligent mattress. The sleep improvement method is applied to an intelligent mattress, the intelligent mattress comprises a mattress body, a dot matrix sensor array and a processor, the mattress body comprises an air bag assembly, and the dot matrix sensor array is electrically connected with the processor; the lattice sensor array is arranged on the mattress body; the lattice type sensor array is used for sensing human body sign information to obtain a sensor dot value graph; the sleep improvement method comprises the following steps: acquiring a sensor point value map; determining current supporting information based on the sensor point value graph, wherein the current supporting information comprises supporting area information and supporting force information; determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting strength information; the amount of gas in the airbag module is adjusted based on the target support information. By adopting the scheme, the effect of improving the sleep of the user by improving the intelligent adjustment precision is realized.)

1. The sleep improvement method is applied to an intelligent mattress, and is characterized in that the intelligent mattress comprises a mattress body, a dot matrix sensor array and a processor, wherein the mattress body comprises an air bag assembly, and the dot matrix sensor array is electrically connected with the processor; the lattice sensor array is arranged on the mattress body; the lattice type sensor array is used for sensing human body sign information to obtain a sensor dot value graph; the sleep improvement method comprises the following steps:

acquiring the sensor point value graph;

determining current supporting information based on the sensor point value graph, wherein the current supporting information comprises supporting area information and supporting strength information;

determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting strength information;

adjusting an amount of gas of the airbag module based on the target support information.

2. The sleep improvement method according to claim 1, characterized in that the sensor point value map comprises sensor point values and sensor point value sizes; the determining current support information based on the sensor point value map comprises:

determining the area of the region of the human body in contact with the mattress body and a support matrix based on the sensor point value graph; the support matrix comprises sensor point positions and sensor point values, wherein the detection values of the sensor point positions are larger than preset detection values;

determining current support information based on the region area and the support matrix.

3. The sleep improvement method according to claim 1, further comprising, after adjusting the amount of gas of the airbag module based on the target support information:

the method comprises the steps of obtaining a second sensor point value graph, determining second supporting information based on the second sensor point value graph, determining second target supporting information based on the second supporting information, and adjusting the gas quantity of the airbag module based on the second supporting information and the second target supporting information until the difference value between the second supporting information and the second target supporting information is smaller than a preset difference value.

4. The sleep improvement method according to claim 2, wherein after determining the area of the region where the human body contacts the mattress body and the support matrix based on the sensor point value map, further comprising:

determining sleeping posture information based on the support matrix;

the determining target support information based on the current support information comprises:

and determining target support information based on the current support information and the sleeping posture information.

5. The sleep improvement method according to claim 4, wherein said determining sleeping posture information based on said support matrix comprises:

carrying out binarization processing on the support matrix based on a preset threshold value to obtain a binarization support matrix;

calculating the similarity of the binarization support matrix and a plurality of preset sleeping posture templates respectively;

and determining the sleeping posture information based on the sleeping posture template with the maximum similarity.

6. The sleep improvement method according to claim 5, wherein the calculating the similarity of the binarized support matrix with a plurality of preset sleeping posture templates respectively comprises:

respectively differentiating the binary support matrix with a plurality of preset sleeping posture templates and then taking the sum of squares;

correspondingly, the determining the sleeping posture information based on the sleeping posture template with the maximum similarity comprises the following steps:

and determining the sleeping posture information based on the sleeping posture template with the minimum square sum result.

7. The sleep improvement method according to claim 5, wherein the determining the sleeping posture information based on the sleeping posture template with the largest similarity comprises:

and determining the sleeping posture information based on the sleeping posture template with the maximum similarity and the area.

8. The sleep improvement method according to claim 7, wherein the determining the sleeping posture information based on the sleeping posture template with the largest similarity and the area of the region comprises:

determining whether the area of the region is within a preset support range;

if so, determining the sleeping posture information as the corresponding sleeping posture of the sleeping posture template with the maximum similarity.

9. The sleep improvement method according to claim 1, wherein the lattice sensor array is further configured to sense human body sign information to obtain a sensor waveform; the sleep improvement method further includes:

acquiring a sensor oscillogram;

determining physiological parameter information based on the sensor waveform map;

determining health indicator information based on the physiological parameter information.

10. The sleep improvement method according to claim 9, wherein the physiological parameter information includes at least one of heart rate information, bed getting time point information, bed getting out time point information, body movement information, respiration information, snore information;

and/or the health index information comprises at least one of sleep quality information, heart rate variability information, respiratory variability information, snoring information, sleep breathing disorder information and chronic disease prediction information.

11. An intelligent mattress, its characterized in that: comprises a mattress body (3), a dot matrix sensor array (2) and a processor (1);

the mattress body (3) comprises an air bag assembly;

the lattice type sensor array (2) is arranged on the mattress body (3); the lattice type sensor array (2) is used for sensing human body sign information to obtain a sensor dot value graph;

the lattice type sensor array (2) is electrically connected with the processor (1);

the processor (1) is configured to perform the sleep improvement method of any one of claims 1-10.

12. The smart mattress of claim 11, wherein the array of lattice sensors (2) comprises an array of lattice piezoceramic sensors.

Technical Field

The embodiment of the invention relates to a sleep improvement technology, in particular to a sleep improvement method and an intelligent mattress.

Background

At present, the comfort level of intelligence mattress when in order to improve the sleep usually reaches the purpose, the mode of intelligent regulation promptly through changing support area and support dynamics. The intelligent adjustment mode is mainly realized by embedding an air bag and adjusting by controlling the inflation and deflation modes. In which the adjusted target value is obtained, the prior art is divided into two ways: the first is that the user inputs parameters of height, weight, age, sex, etc. and then the regulation target value is set by a certain conversion formula; the second is to directly preset a set of inflation target values.

The two modes have certain defects, the first mode is easy to cause error data or missing data when the user parameters are acquired, so that the setting of the intelligent inflation target is deviated, and the problems of data missing, inaccurate data, incorrect data after people replacement and the like can be caused because the parameters input by the user depend on the input of the user; the second approach is less universal because each individual has different physical conditions and requires different intelligent adjustments.

Disclosure of Invention

The invention provides a sleep improvement method and an intelligent mattress, which aim to improve the sleep effect of a user by improving the intelligent adjustment precision.

In a first aspect, an embodiment of the present invention provides a sleep improvement method, which is applied to an intelligent mattress, where the intelligent mattress includes a mattress body, a lattice sensor array and a processor, the mattress body includes an airbag module, and the lattice sensor array and the processor are electrically connected; the lattice sensor array is arranged on the mattress body; the lattice type sensor array is used for sensing human body sign information to obtain a sensor dot value graph; the sleep improvement method comprises the following steps:

acquiring the sensor point value graph;

determining current supporting information based on the sensor point value graph, wherein the current supporting information comprises supporting area information and supporting strength information;

determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting strength information;

adjusting an amount of gas of the airbag module based on the target support information.

In an alternative embodiment of the invention, the sensor point value map comprises sensor point locations and sensor point value sizes; the determining current support information based on the sensor point value map comprises:

determining the area of the region of the human body in contact with the mattress body and a support matrix based on the sensor point value graph; the support matrix comprises sensor point positions and sensor point values, wherein the detection values of the sensor point positions are larger than preset detection values;

determining current support information based on the region area and the support matrix.

In an optional embodiment of the present invention, after the adjusting the amount of gas of the airbag module based on the target supporting information, the method further comprises:

the method comprises the steps of obtaining a second sensor point value graph, determining second supporting information based on the second sensor point value graph, determining second target supporting information based on the second supporting information, and adjusting the gas quantity of the airbag module based on the second supporting information and the second target supporting information until the difference value between the second supporting information and the second target supporting information is smaller than a preset difference value.

In an optional embodiment of the invention, after determining the area of the region where the human body contacts the mattress body and the support matrix based on the sensor point value map, the method further includes:

determining sleeping posture information based on the support matrix;

the determining target support information based on the current support information comprises:

and determining target support information based on the current support information and the sleeping posture information.

In an optional embodiment of the present invention, the determining sleeping posture information based on the support matrix comprises:

carrying out binarization processing on the support matrix based on a preset threshold value to obtain a binarization support matrix;

calculating the similarity of the binarization support matrix and a plurality of preset sleeping posture templates respectively;

and determining the sleeping posture information based on the sleeping posture template with the maximum similarity.

In an optional embodiment of the present invention, the calculating the similarity between the binarized support matrix and the preset sleeping posture templates respectively includes:

respectively differentiating the binary support matrix with a plurality of preset sleeping posture templates and then taking the sum of squares;

correspondingly, the determining the sleeping posture information based on the sleeping posture template with the maximum similarity comprises the following steps:

and determining the sleeping posture information based on the sleeping posture template with the minimum square sum result.

In an optional embodiment of the present invention, the determining sleeping posture information based on the sleeping posture template with the largest similarity includes:

and determining the sleeping posture information based on the sleeping posture template with the maximum similarity and the area.

In an optional embodiment of the present invention, the determining the sleeping posture information based on the sleeping posture template with the largest similarity and the area of the region comprises:

determining whether the area of the region is within a preset support range;

if so, determining the sleeping posture information as the corresponding sleeping posture of the sleeping posture template with the maximum similarity.

In an optional embodiment of the present invention, the lattice sensor array is further configured to sense human body sign information to obtain a sensor waveform; the sleep improvement method further includes:

acquiring a sensor oscillogram;

determining physiological parameter information based on the sensor waveform map;

determining health indicator information based on the physiological parameter information.

In an optional embodiment of the present invention, the physiological parameter information includes at least one of heart rate information, bed getting time point information, body movement information, respiration information, and snore information;

and/or the health index information comprises at least one of sleep quality information, heart rate variability information, respiratory variability information, snoring information, sleep breathing disorder information and chronic disease prediction information.

In a second aspect, an embodiment of the present invention further provides an intelligent mattress, which includes a mattress body, a lattice sensor array, and a processor;

the mattress body comprises an air bag assembly;

the lattice sensor array is arranged on the mattress body; the lattice type sensor array is used for sensing human body sign information to obtain a sensor dot value graph;

the lattice sensor array is electrically connected with the processor;

the processor is configured to execute the sleep improvement method according to any embodiment of the present invention.

In an alternative embodiment of the invention, the array of lattice sensors comprises an array of lattice piezoceramic sensors.

The invention obtains a sensor point value graph by measuring through a dot matrix sensor array, determines the current supporting information based on the sensor point value graph, the current supporting information comprises supporting area information and supporting force information, then determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting force information, finally adjusting the gas quantity of the gas bag component based on the target supporting information to realize intelligent adjustment, since the target supporting force information at this time is determined by the current supporting information of the user, therefore, the flexibility of the scheme is higher compared with the scheme that the target supporting information is set by relying on the user parameters input in advance or a group of target supporting information is directly preset, meanwhile, the precision is high, and the effect of improving the sleep of a user by improving the precision of intelligent adjustment is realized.

Drawings

Fig. 1 is a schematic structural diagram of an intelligent mattress applied in a sleep improvement method according to an embodiment of the present invention;

fig. 2 is a flowchart of a sleep improvement method according to an embodiment of the present invention;

fig. 3 is a sensor dot value graph obtained based on a dot matrix sensor array when a user lies down according to an embodiment of the present invention;

fig. 4 is a flowchart of a sleep improvement method according to a second embodiment of the present invention;

fig. 5 is a flowchart of a sleep improvement method according to a third embodiment of the present invention;

fig. 6 is a sensor dot value graph obtained based on a lattice sensor array when a user lies on his/her side according to a third embodiment of the present invention;

fig. 7 is a waveform diagram of a sensor according to a third embodiment of the present invention.

Wherein, 1, a processor; 2. a lattice sensor array; 3. a mattress body.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.

Example one

Fig. 1 is a schematic structural diagram of an intelligent mattress applied in a sleep improvement method according to an embodiment of the present invention; fig. 2 is a flowchart of a sleep improvement method according to an embodiment of the present invention, where the present embodiment is applicable to a situation where a user sleeps while lying on a bed to improve the sleep of the user, and the method may be performed by an intelligent mattress, as shown in fig. 1, the intelligent mattress includes a mattress body 3, a dot matrix sensor array 2 and a processor 1, the mattress body 3 includes an air bag assembly (not shown), and the dot matrix sensor array 2 and the processor 1 are electrically connected; the lattice type sensor array 2 is arranged on the mattress body 3; the lattice type sensor array 2 is used for sensing human body sign information to obtain a sensor dot value graph; as shown in fig. 2, the sleep improvement method specifically includes the following steps:

and S110, acquiring the sensor point value graph.

Wherein, the gasbag subassembly is inside can fill the gasbag structure of gassing when the intelligence mattress is the gasbag mattress, and the user lies on the mattress body when sleeping, and gasbag subassembly can play the supporting role to the user this moment. When the air bags included in the air bag assembly are inflated or deflated, the softness and hardness of the mattress body sensed by a user are different, and the supporting force of the mattress body sensed by the user is correspondingly different.

The human body physical sign information refers to information generated when a human body lies on the intelligent mattress, for example, the human body has gravity, and the human body physical sign information can be information related to the gravity, and is not specifically limited herein.

The dot matrix sensor array is a dot matrix array formed by a plurality of sensors, fig. 3 is a sensor dot value diagram obtained based on the dot matrix sensor array when a user lies down, as shown in fig. 3, the sensor dot value diagram is a diagram formed by the dot positions of the sensors and the dot values of the sensors.

And S120, determining current supporting information based on the sensor point value graph, wherein the current supporting information comprises supporting area information and supporting force information.

When a human body lies on the mattress body, the position of the human body contacting the mattress body can change the corresponding sensor point value in the dot-matrix sensor array due to the existence of gravity, and the supporting area of the mattress body to the human body, namely the supporting area information can be obtained by determining the number of the sensors of which the sensor point values are changed based on the contact of the human body; the sensor point value can also reflect the supporting force of the mattress body to the human body, namely the supporting force information.

S130, determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting strength information.

The target supporting information can be the target supporting information which is most comfortable to human bodies, most healthy to human bodies and most beneficial to improving sleep quality under the current supporting information according to human engineering or individuals obtained by a large amount of experimental data. Generally, the target support information can be obtained through a large number of experiments and human engineering.

S140, adjusting the gas quantity of the air bag component based on the target supporting information.

Wherein, the gas volume of air bag module is different, and the support area just can corresponding change with the support dynamics, for example air bag module's gas volume is great, and air bag module's support dynamics is great this moment, and air bag module non-deformable when the human body lies on the mattress body, there is the clearance between positions such as the waist of normal human body can and the mattress body to it is less to correspond the regional sensor point value variation of human waist in the dot matrix sensor array, and the support area this moment also can be less. When the gas volume of air bag subassembly is less, the support dynamics of air bag subassembly was less this moment, and air bag subassembly is yielding, when the human body lay on the mattress body, the human body of air bag subassembly easy laminating, human and air bag subassembly's area of contact was great this moment, and then the support area also can be corresponding great. Therefore, the gas quantity of the air bag component is adjusted through the target support information, and the support information of the intelligent mattress can be conveniently adjusted to the target support information.

In the scheme, a sensor point value graph is obtained by measuring through a dot matrix sensor array, current supporting information is determined based on the sensor point value graph, the current supporting information comprises supporting area information and supporting force information, then determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting force information, finally adjusting the gas quantity of the gas bag component based on the target supporting information to realize intelligent adjustment, since the target supporting force information at this time is determined by the current supporting information of the user, therefore, the flexibility of the scheme is higher compared with the scheme that the target supporting information is set by relying on the user parameters input in advance or a group of target supporting information is directly preset, meanwhile, the precision is high, and the effect of improving the sleep of a user by improving the precision of intelligent adjustment is realized.

Example two

Fig. 4 is a flowchart of a sleep improvement method according to a second embodiment of the present invention, which is optimized based on the first embodiment. Optionally, the sensor point value map includes sensor point positions and sensor point value sizes; the determining current support information based on the sensor point value map comprises: determining the area of the region of the human body in contact with the mattress body and a support matrix based on the sensor point value graph; the support matrix comprises sensor point positions and sensor point values, wherein the detection values of the sensor point positions are larger than preset detection values; determining current support information based on the region area and the support matrix. Optionally, after adjusting the amount of gas in the airbag module based on the target supporting information, the method further includes: the method comprises the steps of obtaining a second sensor point value graph, determining second supporting information based on the second sensor point value graph, determining second target supporting information based on the second supporting information, and adjusting the gas quantity of the airbag module based on the second supporting information and the second target supporting information until the difference value between the second supporting information and the second target supporting information is smaller than a preset difference value.

As shown in fig. 4, the method has steps including:

and S210, acquiring the sensor point value graph.

S220, determining the area of a region, in which a human body is in contact with the mattress body, and a support matrix based on the sensor point value diagram, wherein the support matrix comprises sensor points and sensor point values, the detection values of which are greater than preset detection values.

The sensor point position is also called a sensor point position or a sensor point coordinate, the sensor point position can refer to a position where a sensor is located in a sensor point value graph formed by a point array type sensor array, the sensor point value is also called a sensor point amplitude, and the sensor point value can refer to a value which can reflect different pressure values and is detected by the sensor. The detection value refers to a sensor point value detected by the sensor, and when the detection value is larger than a preset detection value, the pressure generated when the human body is detected to be positioned on the mattress body by the sensor at the sensor point position is shown.

When the human body lies on the mattress body, the position of the human body contacting the mattress body can change the corresponding sensor point value in the array of the dot-matrix sensors due to the existence of gravity, and the area of the contact area of the human body and the mattress can be determined based on the number of the sensors changed by the sensor point value. The support matrix is a matrix for recording the point positions of the sensors and the point values of the sensors when a human body is on the mattress body.

And S230, determining current supporting information based on the area of the region and the supporting matrix, wherein the current supporting information comprises supporting area information and supporting strength information.

The current supporting information comprises supporting area information and supporting force information, the area reflects the supporting area, and the supporting matrix reflects the supporting force of different sensor point positions, so that the current supporting information can be determined based on the area and the supporting matrix.

S240, determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting strength information.

And S250, adjusting the gas quantity of the air bag component based on the target supporting information.

In a specific embodiment, the sensor point value map at a certain time is S, the area is S _ area, S _ area = f (S), where f is a conversion relation, and may be the total number of all sensors other than 0 point, or the sum of all points of S. The target support information is Adjust _ target, and the support matrix is A _ area. Adjust _ target = f2(S _ area, a _ area); the area size of the human body support and the supporting force size (namely, the current supporting information) are converted through f2 according to the distribution area and the area amplitude size (namely, the area and the supporting matrix) of the current dot matrix, the target value (namely, the target supporting information) of the distribution area and the supporting force size of the supporting force is set according to human engineering, and the air bag inflation and deflation are optimally and intelligently controlled and adjusted according to the obtained target value.

S260, a second sensor point value graph is obtained, second supporting information is determined based on the second sensor point value graph, second target supporting information is determined based on the second supporting information, and the gas quantity of the airbag module is adjusted based on the second supporting information and the second target supporting information until the difference value between the second supporting information and the second target supporting information is smaller than a preset difference value.

The second sensor dot value map is a sensor dot value map obtained by measuring the dot-matrix sensor array after the gas quantity of the air bag module is adjusted, the second support information is the current support information after the gas quantity of the air bag module is adjusted, and the second target support information is the target support information after the gas quantity of the air bag module is adjusted. When the difference value between the second supporting information and the second target supporting information is smaller than a preset difference value, the air bag assembly is adjusted to a better air quantity, and the intelligent mattress has better supporting strength and supporting range for the human body.

After the gas quantity of the air bag assembly is adjusted based on the target support information, the adjusted support information does not necessarily reach the target support information, at the moment, the second sensor point value graph is obtained again, the second support information is determined again, the second target support information is further determined, the gas quantity of the air bag assembly is adjusted based on the second support information and the second target support information until the difference value between the second support information and the second target support information is smaller than the preset difference value, the fact that the result of the inflation and deflation adjustment of the air bag assembly is fed back in real time is achieved, and the adjustment result is better.

EXAMPLE III

Fig. 5 is a flowchart of a sleep improvement method according to a third embodiment of the present invention, which is optimized based on the second embodiment. Optionally, after determining the area of the region where the human body contacts the mattress body and the support matrix based on the sensor point value map, the method further includes: determining sleeping posture information based on the support matrix; the determining target support information based on the current support information comprises: and determining target support information based on the current support information and the sleeping posture information. Optionally, the lattice sensor array is further configured to sense human body sign information to obtain a sensor oscillogram; the sleep improvement method further includes: acquiring a sensor oscillogram; determining physiological parameter information based on the sensor waveform map; determining health indicator information based on the physiological parameter information.

As shown in fig. 5, the method has steps including:

and S310, acquiring the sensor point value graph.

S320, determining the area of the contact area of the human body and the mattress body and a support matrix based on the sensor point value diagram, wherein the support matrix comprises sensor point positions and sensor point values, the detection values of which are larger than preset detection values.

And S330, determining sleeping posture information based on the support matrix.

The shape formed by the contact area of different parts of the user and the intelligent mattress under different sleeping postures can be different, and the pressure applied to the intelligent mattress when each part contacts the intelligent mattress can be correspondingly different, so that the sleeping posture of the user can be conveniently and accurately determined according to the support matrix.

S340, determining current supporting information based on the area of the region and the supporting matrix, wherein the current supporting information comprises supporting area information and supporting strength information.

S350, determining target supporting information based on the current supporting information and the sleeping posture information, wherein the target supporting information comprises target supporting area information and target supporting strength information.

Wherein, same user all can corresponding difference at the appearance condition of sleeping of difference bracing force and support area, combines the appearance information of sleeping to confirm target support information through current support information, and the target support information that obtains is comparatively accurate, the user demand of matching user that can be better. For example, fig. 3 is a sensor point value graph obtained based on a lattice sensor array when a user lies down according to an embodiment of the present invention; fig. 6 is a sensor dot value graph obtained based on a lattice sensor array when a user lies on his/her side according to a third embodiment of the present invention; as shown in fig. 3 and 6, the supporting force and the supporting area of the user are different correspondingly in different sleeping postures, and the obtained sensor point value graph is also different correspondingly.

And S360, adjusting the gas quantity of the air bag assembly based on the target supporting information.

S370, a second sensor point value graph is obtained, second supporting information is determined based on the second sensor point value graph, second target supporting information is determined based on the second supporting information, and the gas quantity of the airbag module is adjusted based on the second supporting information and the second target supporting information until the difference value between the second supporting information and the second target supporting information is smaller than a preset difference value.

And S380, acquiring a sensor oscillogram.

The waveform diagram is a curve reflecting different displacements of the particles at the same time, and is called a wave image. The waveform plot is used to display one or more curves of measured values as uniformly collected. The sensor waveform plots are voltage value curves of the sensor at different times.

And S390, determining physiological parameter information based on the sensor oscillogram.

The lattice sensor array can detect the micro motion of human body in different positions and convert into electric signal, so that the physiological parameter information of the user may be obtained conveniently based on the sensor waveform. In a specific embodiment, the physiological parameter information includes at least one of heart rate information, bed getting time point information, body movement information, respiration information and snore information. The different specific information also has different ways of acquiring the physiological parameter information. For example, fig. 7 is a sensor waveform diagram according to a third embodiment of the present invention, as shown in fig. 7, for a sensor waveform diagram at a certain time, information about heartbeat, information about snoring and information about respiration of a user can be extracted at different positions of the sensor waveform diagram, and further related heart rate information, respiration information, body movement information, snoring information and the like can be obtained.

And S400, determining health index information based on the physiological parameter information.

In a specific embodiment, the health indicator information comprises at least one of sleep quality information, heart rate variability information, respiratory variability information, snoring information, sleep disordered breathing information, chronic disease prediction information.

The sleep quality information (the reasonability of cycles such as sleep duration (getting on and off a bed point), deep and shallow sleep (heart rate breathing movement) and the like, the snoring times energy and the times and the degree of breathing disorder generation and the sleep quality obtained by comprehensive conversion) is obtained, for example, the sleep duration of a user can be obtained according to the time point information of getting on the bed and the time point information of getting off the bed, the movement condition in the sleep process can be obtained through the movement information, the heart rate variability information is comprehensively given according to time domain and frequency domain characteristics of long-time statistical heart rate intervals, the breathing variability information can be obtained according to the breathing information of different time periods, the snoring information of the user can be obtained according to the snoring sound information, and the chronic disease prediction information is also obtained by synthesizing all information and carrying out self-learning through building an algorithm model.

It should be noted that the above sequence numbers do not represent a specific execution sequence, and for example, S370 and S380 may be sequentially executed according to the execution procedure in the above embodiment. Alternatively, S310 and S380 may be performed simultaneously, that is, the sensor waveform map is obtained while the sensor point value map is obtained; alternatively, S380 may be performed before S310, that is, after the sensor waveform map is acquired, the sensor point value map is acquired. The execution order of the steps may be various, and is not particularly limited as long as the execution order of S390 and S400 is after S380 while the execution order of S320-S370 is after S310.

On the basis of the above embodiment, the determining sleeping posture information based on the support matrix includes:

carrying out binarization processing on the support matrix based on a preset threshold value to obtain a binarization support matrix; calculating the similarity of the binarization support matrix and a plurality of preset sleeping posture templates respectively; and determining the sleeping posture information based on the sleeping posture template with the maximum similarity.

The binarization processing means that each sensor point value in the support matrix is converted into 0 and 1, the preset threshold value means a standard value used for judging 0 and 1, the sensor point value is judged to be 1 when being larger than the preset threshold value, and the sensor point value is judged to be 0 when being smaller than the preset threshold value, and the support matrix is processed in this way, so that the binarization support matrix can be obtained. The preset sleeping posture templates are binary matrix templates with only 0 and 1, and the similarity between the binary support matrix and the preset sleeping posture templates is calculated, so that the sleeping posture information of the user can be conveniently obtained. When the similarity between the binary support matrix and a certain sleeping posture template is maximum, the fact that the user is most likely to be the sleeping posture corresponding to the current sleeping posture template is demonstrated, and therefore the sleeping posture information can be conveniently determined based on the sleeping posture template with the maximum similarity.

Specifically, calculating the similarity between the binarized support matrix and a plurality of preset sleeping posture templates respectively comprises: respectively differentiating the binary support matrix with a plurality of preset sleeping posture templates and then taking the sum of squares; correspondingly, the determining the sleeping posture information based on the sleeping posture template with the maximum similarity comprises the following steps: and determining the sleeping posture information based on the sleeping posture template with the minimum square sum result.

The binarization support matrix is differentiated from the preset sleeping posture templates respectively and then the sum of squares is taken, so that the difference degree between the binarization support matrix and the different preset sleeping posture templates can be conveniently judged, and the similarity between the binarization support matrix and the different preset sleeping posture templates is obtained. When the square sum result is minimum, the difference degree between the binarization support matrix and the preset sleeping posture template is smaller, that is, the similarity between the binarization support matrix and the preset sleeping posture template is maximum, so that the sleeping posture information can be conveniently determined.

In an optional embodiment of the present invention, the determining sleeping posture information based on the sleeping posture template with the largest similarity includes: and determining the sleeping posture information based on the sleeping posture template with the maximum similarity and the area.

The area of the region is the area of all the sensor points that are subjected to pressure from the user, and since the sensor point value map is composed of the sensor points and the sensor point values of all the sensors at a certain time, the area of the region can be determined based on the sensor point value map. The sleeping area of a normal person is within a certain range, namely the area of the region is within a certain range, the sleeping posture information is determined by combining the sleeping posture template with the maximum similarity with the area of the region, the normal sleeping and the non-sleeping (interference of other objects such as quilts, pillows and the like) of the person can be distinguished, the range of the area size of the region when the person actually sleeps is obtained through quantitative experiments for judgment, and the accuracy of determining the sleeping posture information is improved.

On the basis of the above embodiment, the determining the sleeping posture information based on the sleeping posture template with the largest similarity and the area includes: determining whether the area of the region is within a preset support range; if so, determining the sleeping posture information as the corresponding sleeping posture of the sleeping posture template with the maximum similarity.

The preset support range is the range of the area size when the person normally sleeps, whether the person normally sleeps can be known by determining whether the area of the area is in the preset support range, if so, the sleeping posture of the user can be judged, so that the sleeping posture information can be determined to be the corresponding sleeping posture of the sleeping posture template with the maximum similarity, the accuracy of sleeping posture identification is improved, and false identification is prevented.

Example four

The fourth embodiment of the invention also provides an intelligent mattress, as shown in fig. 1, the intelligent mattress comprises a mattress body 3, a lattice sensor array 2 and a processor 1;

the mattress body 3 includes an air bag module (not shown in the drawings);

the lattice type sensor array 2 is arranged on the mattress body 3; the lattice type sensor array 2 is used for sensing human body sign information to obtain a sensor dot value graph;

the lattice type sensor array 2 is electrically connected with the processor 1;

the processor 1 is configured to execute the sleep improvement method according to any of the embodiments of the present invention.

In the scheme, the dot value graph of the sensor is obtained by setting the dot-matrix sensor array 2 for detection, the processor 1 determines the current supporting information based on the dot value graph of the sensor, the current supporting information comprises supporting area information and supporting force information, then determining target supporting information based on the current supporting information, wherein the target supporting information comprises target supporting area information and target supporting force information, finally adjusting the gas quantity of the gas bag component based on the target supporting information to realize intelligent adjustment, since the target supporting force information at this time is determined by the current supporting information of the user, therefore, the flexibility of the scheme is higher compared with the scheme that the target supporting information is set by relying on the user parameters input in advance or a group of target supporting information is directly preset, meanwhile, the precision is high, and the effect of improving the sleep of a user by improving the precision of intelligent adjustment is realized.

In an alternative embodiment of the invention, the array of lattice sensors 2 comprises an array of lattice piezoceramic sensors.

Wherein, dot matrix piezoceramics sensor array indicates the dot matrix array of constituteing through a plurality of piezoceramics sensors, piezoceramics sensor's advantage: economical, good signal relative to thin film, and small mutual interference. Therefore, the piezoelectric ceramic sensor array is formed by the piezoelectric ceramic sensors, the interference on detection is small, and the piezoelectric ceramic sensor array is economical and has good signals.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.