Human health monitoring system and method based on flexible sensor

Abstract

The invention discloses a human body health monitoring system and method based on a flexible sensor, relates to the technical field of material science, and solves the problems that in the prior art, the human body health state is evaluated through the comprehensive control effect of health indexes and the fluctuation condition of the health indexes, and the influence of multiple factors on human body health is not considered; the problem that the evaluation result is inaccurate is solved. According to the invention, user-defined setting is carried out on the flexible sensor according to user requirements; external stimulation conversion electric signals are recorded according to the flexible sensor, and scores are assigned to various physiological difference values; the daily comprehensive health value of the user is obtained according to the assignment value of each physiological difference value; obtaining a normal health threshold value from the database, and judging whether the comprehensive health value is lower than the normal health threshold value or not; if yes, recording and counting the ratio of the number of days when the comprehensive health value is lower than the normal health threshold value; if not, continuing to judge; evaluating the health level of the user according to the day number ratio; the human health state can be evaluated more comprehensively and objectively.

Description

Technical Field

[0001] The present invention belongs to the field of material science and relates to sensor technology, in particular to a human health monitoring system and method based on flexible sensors. Background Art

[0002] Flexible sensors can fit closely to the human body and monitor various physiological indicators in real time, such as heart rate, blood pressure, body temperature, respiratory rate, etc., to provide instant health data; through real-time analysis of monitoring data, the system can issue timely warnings when health indicators are abnormal, which is helpful for early detection and intervention of potential health problems; health ratings can help to achieve the rational allocation of medical resources, so that medical resources can be more inclined to people in need, and the efficiency and quality of medical services can be improved; the application of flexible sensors in the field of health monitoring has promoted the innovation and development of medical technology and provided a new growth point for the future medical and health industry.

[0003] The prior art (invention patent application with publication number CN106446536A) discloses a method for evaluating human health status, including: obtaining historical detection data of the analyzed health indicators within a set time range; analyzing the historical detection data to obtain the comprehensive control effect of the health indicators; and analyzing the historical detection data to obtain the fluctuation of the health indicators; comprehensively analyzing the comprehensive control effect of the health indicators and the fluctuation of the health indicators to evaluate the final human health status; the prior art evaluates the final human health status through the comprehensive control effect of the health indicators and the fluctuation of the health indicators, but does not take into account that human health is affected by many factors, which may lead to inaccurate evaluation results.

[0004] The present invention provides a human health monitoring system and method based on a flexible sensor to solve the above technical problems. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a human health monitoring system and method based on flexible sensors, which is used to solve the problem that the prior art obtains the final human health status through the comprehensive control effect of health indicators and the fluctuation of the health indicators, but does not take into account that human health is affected by many factors, which may lead to inaccurate evaluation results.

[0006] To achieve the above-mentioned object, a first aspect of the present invention provides a human health monitoring system based on a flexible sensor, comprising: a flexible sensing module, a health analysis module and a user interface module;

[0007] Flexible sensing module: Obtain user needs and customize the flexible sensor according to user needs; perceive external stimuli through electronic skin, convert external stimuli into electrical signals according to flexible sensors for recording, and generate several physiological change tables; external stimuli include: pressure, temperature, humidity; various physiological changes include: changes in blood pressure, heart rate, body temperature, and electromyography;

[0008] Health analysis module: obtain the difference of each physiological change through each physiological change table and assign points to each physiological difference; obtain the user's daily comprehensive health value based on the assigned value of each physiological difference; obtain the normal health threshold from the database to determine whether the comprehensive health value is lower than the normal health threshold; if yes, record and count the proportion of days when the comprehensive health value is lower than the normal health threshold; if not, continue to judge; evaluate the user's health level based on the proportion of days.

[0009] Preferably, the system further includes a user interface module: used to store various physiological differences of the user and display the assessed user health level, and to send out early warning signals and reminder signals.

[0010] The present invention constructs a user interface module so that users can view their physiological data and health level in real time, which is helpful for users to understand their health status in a timely manner; the system evaluates the user's health level according to preset health standards and provides users with instant health feedback.

[0011] Preferably, obtaining each physiological change difference through each physiological change table and assigning points to each physiological difference includes:

[0012] Retrieve various physiological change tables and mark the maximum values ​​of blood pressure, heart rate, body temperature, and myoelectricity as XYi max 、XTi max 、TWi max 、JDi max ; Mark the minimum values ​​of blood pressure, heart rate, body temperature, and electromyography as XYi min 、XTi min 、TWi min 、JDi min ; Wherein, i represents a specific number of days, and i is a positive integer;

[0013] Through the formula XYi=XYi max -XYi min The blood pressure difference is calculated;

[0014] By the formula XTi=XTi max -XTi min Calculate the heartbeat difference;

[0015] By the formula TWi=TWi max-TWi min Calculate the body temperature difference;

[0016] By the formula JDi=JDi max -JDi min The myoelectric difference is calculated;

[0017] Obtain the normal physiological difference ranges of each item from the database, and determine whether the difference of each physiological change is within the normal physiological difference range of the corresponding item; if yes, assign the corresponding physiological difference value ZFj, and mark CFj as 0; if not, assign the corresponding physiological difference value CFj, and mark ZFj as 0; wherein ZFj and CFj are both integers greater than 0 and less than or equal to 100, and ZFj-CFj>T; wherein j represents the assigned value of different physiological differences, and j=1,2,3,4; T is the difference value.

[0018] It should be noted that in order to better distinguish between the two situations where the difference between each physiological change is lower than the normal physiological difference range of the corresponding item and the difference between each physiological change is higher than the normal physiological difference range of the corresponding item; the value range of the distinction difference T is set: 50<T<100; the myoelectric value here refers to the insertion reaction duration.

[0019] The present invention can accurately assess whether the user's physiological state deviates from the normal state by calculating the difference of various physiological changes and comparing them with the normal range. This accuracy helps to detect potential health problems at an early stage. The setting of ZFj and CFj allows the scoring rules to be adjusted according to specific circumstances to adapt to different users or different health needs. At the same time, by setting the T value to distinguish between situations below and above the normal range, the flexibility and accuracy of the scoring mechanism are increased.

[0020] Preferably, the user's daily comprehensive health value is obtained according to the scoring values ​​of each physiological difference, including:

[0021] Retrieve the scoring values ​​of each normal physiological difference range of the user every day;

[0022] The user's daily comprehensive health value is calculated by the formula ZHZi=(ZF1+CF1)×a1+(ZF2+CF2)×a2+(ZF3+CF3)×a3+(ZF4+CF4)×a4; wherein a1, a2, a3, and a4 are proportional coefficients greater than 0 and less than 1 respectively.

[0023] The present invention is conducive to reflecting the importance of different physiological indicators in comprehensive health assessment by determining weight coefficients; and better reflects the overall health status of the user on that day by calculating the comprehensive health value.

[0024] Preferably, the recording and counting of the percentage of days when the comprehensive health value is lower than the normal health threshold value includes:

[0025] Set the statistical period of days and mark it as TZ, and mark the days when the comprehensive health value is lower than the normal health threshold as DT; where TZ and DT are both positive integers, and TZ ≥ DT;

[0026] The day percentage is calculated using the formula TZL=(DT / TZ)×100%.

[0027] It should be noted that the statistical period of days is set manually according to actual conditions.

[0028] The present invention makes data comparable between different time periods by setting a fixed statistical cycle of days; when TZL is high, it means that there are more days with poor health status in the statistical cycle, which serves as a signal to trigger health management and intervention measures.

[0029] Preferably, the step of evaluating the user's health level according to the percentage of days includes:

[0030] The percentage of days is retrieved. When TZL>60%, the user's health level is marked as level 1, and an early warning signal is issued to remind the user to undergo a physical examination;

[0031] When 40%<TZL≤60%, the user health level is marked as level 2; if the user health level is level 2 for more than two consecutive statistical cycles, it is predicted and judged whether the user health level will change to level 1 in the next statistical cycle; if yes, a reminder signal is issued; if no, the judgment is continued;

[0032] When TZL≤40%, the user's health level is marked as level three.

[0033] The present invention can provide a personalized health assessment for a user by calculating the day proportion; moreover, different day proportions reflect the health status of the user in different time periods, thereby being able to more accurately judge the health status of the user.

[0034] Preferably, the predicting and judging whether the user health level of the user will be changed to level 1 in the next day statistical cycle includes:

[0035] Retrieve the statistical period of days when the user's health level is level 2 for more than two consecutive days and mark it as TZ n , and construct a statistical period table of days in level 2, where n is the number of statistical periods in which the health level of the user is level 2, and n is an integer greater than 2; by formula Bm=TZ n+1 -TZ nCalculate the slope value between every two adjacent days statistical cycles; where m is the number of slope values, and m is a positive integer greater than 0; determine whether Bm is always greater than 0; if yes, predict that the user's user health level will change to level one in the next days statistical cycle; if no, predict that the user's user health level will not change to level one in the next days statistical cycle.

[0036] The present invention can quantify the trend of changes in the user's health level by calculating the slope value between every two adjacent days statistical cycles; when all slope values ​​are greater than 0, it indicates that the user's health level is continuously deteriorating, thereby improving the accuracy of predicting that the user's health level may change to level one in the next cycle.

[0037] To achieve the above object, the second aspect of the present invention provides a human health monitoring method based on a flexible sensor, comprising:

[0038] Obtain user needs and customize the flexible sensor according to user needs; perceive external stimuli through electronic skin, convert external stimuli into electrical signals according to flexible sensors for recording, and generate several physiological change tables; external stimuli include: pressure, temperature, humidity; various physiological changes include: changes in blood pressure, heart rate, body temperature, and electromyography;

[0039] Through various physiological change tables, the difference of various physiological changes is obtained and each physiological difference is scored; according to the scored value of each physiological difference, the user's daily comprehensive health value is obtained; the normal health threshold is obtained from the database to determine whether the comprehensive health value is lower than the normal health threshold; if yes, record and count the proportion of days when the comprehensive health value is lower than the normal health threshold; if not, continue to judge; evaluate the user's health level according to the proportion of days.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. The present invention uses a flexible sensing module to perform customized settings according to user needs, which makes health monitoring more personalized and accurate. Different users can choose the physiological parameters and external stimuli that need to be monitored according to their own health conditions and concerns, so as to obtain more targeted health data; the health analysis module can scientifically evaluate the user's health status by assigning points to the differences in various physiological changes and calculating the comprehensive health value; at the same time, the system can determine whether the comprehensive health value is lower than the normal health threshold, and send out a warning signal when necessary to remind the user to pay attention to his or her own health.

[0042] 2. The present invention can record the user's physiological changes in real time, including four key indicators: blood pressure, heart rate, body temperature, and electromyography. This real-time nature ensures the timeliness and accuracy of health data, and helps to timely discover potential health problems. The present invention records and counts the proportion of days when the comprehensive health value is lower than the normal health threshold, thereby achieving long-term tracking and evaluation of the user's health status. This long-term nature helps to discover health trends and potential health problems, and provides a basis for formulating personalized health management plans. Moreover, the user's health level is evaluated based on the proportion of days, and feedback is provided to the user. This feedback mechanism helps the user understand his or her own health status and take corresponding health management measures based on the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A schematic diagram of a module structure in a health monitoring system of the present invention;

[0045] Figure 2 A schematic diagram of the specific steps of the health analysis of the present invention;

[0046] Figure 3 It is a schematic diagram of the process of the health monitoring method of the present invention. DETAILED DESCRIPTION

[0047] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] See also Figure 1 , the first aspect of the present invention provides a human health monitoring system and method based on a flexible sensor, including: a flexible sensing module, a health analysis module and a user interface module;

[0049] Flexible sensing module: Obtain user needs and customize the flexible sensor according to user needs; perceive external stimuli through electronic skin, convert external stimuli into electrical signals according to flexible sensors for recording, and generate several physiological change tables; external stimuli include: pressure, temperature, humidity; various physiological changes include: changes in blood pressure, heart rate, body temperature, and electromyography;

[0050] Health analysis module: obtain the difference of each physiological change through each physiological change table and assign points to each physiological difference; obtain the user's daily comprehensive health value based on the assigned value of each physiological difference; obtain the normal health threshold from the database to determine whether the comprehensive health value is lower than the normal health threshold; if yes, record and count the percentage of days when the comprehensive health value is lower than the normal health threshold; if no, continue to determine; evaluate the user's health level based on the percentage of days;

[0051] User interface module: used to store the user's various physiological differences and display the user's health level after evaluation, and send out early warning signals and reminder signals.

[0052] See also Figure 2 , the specific steps of health analysis, call up various physiological change tables, and mark the maximum values ​​of blood pressure, heart rate, body temperature, and electromyography as XYi max 、XTi max 、TWi max 、JDi max ; Mark the minimum values ​​of blood pressure, heart rate, body temperature, and electromyography as XYi min 、XTi min 、TWi min 、JDi min ; Wherein, i represents a specific number of days, and i is a positive integer;

[0053] Through the formula XYi=XYi max -XYi min The blood pressure difference is calculated;

[0054] By the formula XTi=XTi max -XTi min Calculate the heartbeat difference;

[0055] By the formula TWi=TWi max -TWi min Calculate the body temperature difference;

[0056] By the formula JDi=JDi max -JDi min The myoelectric difference is calculated;

[0057] Obtain the normal physiological difference ranges of each item from the database, and determine whether the difference of each physiological change is within the normal physiological difference range of the corresponding item; if yes, assign the corresponding physiological difference to ZFj, and mark CFj as 0; if no, assign the corresponding physiological difference to CFj, and mark ZFj as 0; wherein ZFj and CFj are both integers greater than 0 and less than or equal to 100, and ZFj-CFj>T; wherein j represents the assigned value of different physiological differences, and j=1,2,3,4; T is the difference;

[0058] The user's daily comprehensive health value is calculated by the formula ZHZi=(ZF1+CF1)×a1+(ZF2+CF2)×a2+(ZF3+CF3)×a3+(ZF4+CF4)×a4; where a1, a2, a3, and a4 are proportional coefficients greater than 0 and less than 1 respectively;

[0059] Obtain the normal health threshold from the database and determine whether the comprehensive health value is lower than the normal health threshold; if yes, set the day statistical period and mark it as TZ, and mark the days when the comprehensive health value is lower than the normal health threshold as DT; where TZ and DT are both positive integers, and TZ ≥ DT; calculate the day proportion by the formula TZL = (DT / TZ) × 100%; if no, continue to determine;

[0060] The percentage of days is retrieved. When TZL>60%, the user's health level is marked as level 1, and an early warning signal is issued to remind the user to undergo a physical examination;

[0061] When 40%<TZL≤60%, the user health level is marked as level 2; retrieve the statistical period of days when the user health level is level 2 for more than two consecutive days and mark it as TZ n , and construct a statistical period table of days in level 2, where n is the number of statistical periods in which the health level of the user is level 2, and n is an integer greater than 2; by formula Bm=TZ n+1 -TZ n Calculate the slope value between every two adjacent days statistical cycles; where m is the number of slope values, and m is a positive integer greater than 0; determine whether Bm is always greater than 0; if yes, predict that the user's user health level will change to level one in the next days statistical cycle; if no, predict that the user's user health level will not change to level one in the next days statistical cycle.

[0062] When TZL≤40%, the user's health level is marked as level three.

[0063] For example, we need to analyze the health status of user A within 21 days. We have a tri-modal flexible sensor that converts external stimuli to generate 84 physiological change tables, including blood pressure, heart rate, body temperature, and myoelectric insertion reaction duration.

[0064] The maximum and minimum values ​​of blood pressure, heart rate, body temperature, and muscle insertion reaction duration were obtained from the physiological change table. The maximum values ​​of blood pressure, heart rate, body temperature, and muscle insertion reaction duration on the first day were recorded as: 140 mmHg, 147 times, 37.4°C, and 2.2 seconds; the minimum values ​​of blood pressure, heart rate, body temperature, and muscle insertion reaction duration on the first day were recorded as: 10 mmHg, 67 times, 37.2°C, and 1.5 seconds;

[0065] The blood pressure difference, heart rate difference, body temperature difference, and myoelectric difference calculated by the formula were 37 mmHg, 80 times, 0.2°C, and 0.7 seconds respectively;

[0066] Among them, the normal blood pressure difference in a day is 20-30mmHg; the heart rate difference is 40 minutes / beat; the body temperature difference is 1℃; the normal muscle insertion reaction lasts no more than 2 seconds;

[0067] Compared with the normal difference, the temperature difference and myoelectric difference of user A on the first day are within the normal difference range, so the corresponding physiological difference ZF3 and ZF4 are scored as 100 points, and CF3 and CF4 are marked as 0; while the blood pressure difference and heart rate difference are not within the normal difference range, so the corresponding physiological difference CF1 and CF2 are scored as 20 points, and ZF1 and ZF2 are marked as 0 points; a1, a2, a3, and a4 are all marked as 0.2;

[0068] The formula ZHZi=(0+20)×0.2+(0+20)×0.2+(100+0)×0.2+(100+0)×0.2 is used to calculate that the comprehensive health value of user A on the first day is 48 points;

[0069] According to the above calculation steps, the comprehensive health values ​​of user A in 21 days are 48 points, 64 points, 48 ​​points, 32 points, 80 points, 32 points, 64 points, 16 points, 32 points, 80 points, 32 points, 64 points, 16 points, 48 ​​points, 64 points, 48 ​​points, 64 points, 16 points, 48 ​​points, 48 ​​points, and 32 points respectively; the statistical period is set to 7 days, and the comprehensive health values ​​of the above 21 days are divided into three groups;

[0070] Among them, the first group: 48 points, 32 points, 48 ​​points, 32 points, 80 points, 32 points, 64 points;

[0071] Group 2: 16 points, 32 points, 80 points, 32 points, 64 points, 16 points, 48 ​​points;

[0072] Group 3: 64 points, 48 ​​points, 32 points, 16 points, 48 ​​points, 48 ​​points, 32 points;

[0073] The normal health threshold score obtained from the database is 45 points; the number of days that the comprehensive health value of the first group is lower than the normal health threshold is 3 days; the number of days that the comprehensive health value of the second group is lower than the normal health threshold is 4 days; the number of days that the comprehensive health value of the third group is lower than the normal health threshold is 3 days;

[0074] By using the formula TZL = (DT / TZ) × 100%, we can calculate that the first group of days accounts for 42.9%; the second group of days accounts for 58.1%; and the third group of days accounts for 42.9%. Therefore, the health level of user A is level 2 in all three periods.

[0075] Now, a statistical period table of days for level 2 is constructed. By using the formula (58.-42.9) / 1, it is calculated that B1=15.2; B2=-15.2<0, and it is predicted that the user health level of user A will not be changed to level 1 in the next statistical period of days.

[0076] See also Figure 3 The second aspect of the present invention provides a human health monitoring method based on a flexible sensor, comprising:

[0077] Obtain user needs and customize the flexible sensor according to user needs; perceive external stimuli through electronic skin, convert external stimuli into electrical signals according to flexible sensors for recording, and generate several physiological change tables; external stimuli include: pressure, temperature, humidity; various physiological changes include: changes in blood pressure, heart rate, body temperature, and electromyography;

[0078] Through various physiological change tables, the difference of various physiological changes is obtained and each physiological difference is scored; according to the scored value of each physiological difference, the user's daily comprehensive health value is obtained; the normal health threshold is obtained from the database to determine whether the comprehensive health value is lower than the normal health threshold; if yes, record and count the proportion of days when the comprehensive health value is lower than the normal health threshold; if not, continue to judge; evaluate the user's health level according to the proportion of days.

[0079] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0080] The working principle of the present invention is as follows: the present invention obtains user needs and customizes flexible sensors according to user needs; senses external stimuli through electronic skin, converts external stimuli into electrical signals according to flexible sensors for recording, and generates several physiological change tables to obtain various physiological change differences through various physiological change tables and assign points to various physiological differences; obtains the user's daily comprehensive health value according to the assigned values ​​of various physiological differences; obtains the normal health threshold from the database to determine whether the comprehensive health value is lower than the normal health threshold; if yes, records and counts the proportion of days when the comprehensive health value is lower than the normal health threshold; if not, continues to determine; and evaluates the user's health level according to the proportion of days.

[0081] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A human health monitoring system based on flexible sensors, characterized in that: include: Flexible sensing module, health analysis module and user interface module; Flexible sensing module: obtain user needs and customize the flexible sensor according to user needs; The electronic skin senses external stimuli, converts them into electrical signals based on flexible sensors for recording, and generates several physiological change tables; External stimuli include pressure, temperature, and humidity; physiological changes include changes in blood pressure, heart rate, body temperature, and electromyography; Health analysis module: obtain the difference of each physiological change through each physiological change table and assign points to each physiological difference; obtain the user's daily comprehensive health value based on the assigned value of each physiological difference; obtain the normal health threshold from the database to determine whether the comprehensive health value is lower than the normal health threshold; if yes, record and count the proportion of days when the comprehensive health value is lower than the normal health threshold; if not, continue to judge; evaluate the user's health level based on the proportion of days.

2. A human health monitoring system based on a flexible sensor according to claim 1, characterized in that: The system further comprises a user interface module: It is used to store various physiological differences of the user and display the user's health level after evaluation, and send out early warning and reminder signals.

3. A human health monitoring system based on a flexible sensor according to claim 1, characterized in that: The step of obtaining each physiological change difference through each physiological change table and assigning points to each physiological difference includes: Retrieve various physiological change tables and mark the maximum values ​​of blood pressure, heart rate, body temperature, and myoelectricity as XYi max 、XTi max 、TWi max 、JDi max ; Mark the minimum values ​​of blood pressure, heart rate, body temperature, and electromyography as XYi min 、XTi min 、TWi min 、JDi min ; Wherein, i represents a specific number of days, and i is a positive integer; Through the formula XYi=XYi max -XYi min The blood pressure difference is calculated; By the formula XTi=XTi max -XTi min Calculate the heartbeat difference; By the formula TWi=TWi max -TWi min Calculate the body temperature difference; By the formula JDi=JDi max -JDi min The myoelectric difference is calculated; Obtain the normal physiological difference ranges of each item from the database, and determine whether the difference of each physiological change is within the normal physiological difference range of the corresponding item; if yes, assign the corresponding physiological difference value ZFj, and mark CFj as 0; if not, assign the corresponding physiological difference value CFj, and mark ZFj as 0; wherein ZFj and CFj are both integers greater than 0 and less than or equal to 100, and ZFj-CFj>T; wherein j represents the assigned value of different physiological differences, and j=1,2,3,4; T is the difference value.

4. The human health monitoring system based on flexible sensors according to claim 1, characterized in that: The user's daily comprehensive health value is obtained based on the scoring of each physiological difference, including: Retrieve the scoring values ​​of each normal physiological difference range of the user every day; The user's daily comprehensive health value is calculated by the formula ZHZi=(ZF1+CF1)×a1+(ZF2+CF2)×a2+(ZF3+CF3)×a3+(ZF4+CF4)×a4; wherein a1, a2, a3, and a4 are proportional coefficients greater than 0 and less than 1 respectively.

5. The human health monitoring system based on flexible sensors according to claim 1, characterized in that: The recording and statistics of the percentage of days when the comprehensive health value is lower than the normal health threshold include: Set the statistical period of days and mark it as TZ, and mark the days when the comprehensive health value is lower than the normal health threshold as DT; where TZ and DT are both positive integers, and TZ ≥ DT; The day percentage is calculated by the formula TZL=(DT / TZ)×100%.

6. The human health monitoring system based on flexible sensors according to claim 1, characterized in that: The user health level is evaluated based on the proportion of days, including: The percentage of days is retrieved. When TZL>60%, the user's health level is marked as level 1, and an early warning signal is issued to remind the user to undergo a physical examination; When 40%<TZL≤60%, the user health level is marked as level 2; if the user health level is level 2 for more than two consecutive statistical cycles, it is predicted and judged whether the user health level will change to level 1 in the next statistical cycle; if yes, a reminder signal is issued; if no, the judgment is continued; When TZL≤40%, the user's health level is marked as level three.

7. A human health monitoring system based on a flexible sensor according to claim 6, characterized in that: The predicting and judging whether the user health level of the user will be changed to level 1 in the next day statistical cycle includes: Retrieve the statistical period of days when the user's health level is level 2 for more than two consecutive days and mark it as TZ n , and construct a statistical period table of days in level 2, where n is the number of statistical periods in which the health level of the user is level 2, and n is an integer greater than 2; by formula Bm=TZ n+1 -TZ n Calculate the slope value between every two adjacent days statistical cycles; where m is the number of slope values, and m is a positive integer greater than 0; determine whether Bm is always greater than 0; if yes, predict that the user's user health level will change to level one in the next days statistical cycle; if no, predict that the user's user health level will not change to level one in the next days statistical cycle.

8. A human health monitoring method based on a flexible sensor, applied to a human health monitoring system based on a flexible sensor according to any one of claims 1 to 7, characterized in that: include: Obtain user requirements and customize the flexible sensor according to user requirements; The electronic skin senses external stimuli, converts them into electrical signals based on flexible sensors for recording, and generates several physiological change tables; External stimuli include pressure, temperature, and humidity; physiological changes include changes in blood pressure, heart rate, body temperature, and electromyography; Through various physiological change tables, the difference of various physiological changes is obtained and each physiological difference is scored; according to the scored value of each physiological difference, the user's daily comprehensive health value is obtained; the normal health threshold is obtained from the database to determine whether the comprehensive health value is lower than the normal health threshold; if yes, record and count the proportion of days when the comprehensive health value is lower than the normal health threshold; if not, continue to judge; evaluate the user's health level according to the proportion of days.

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