TWM578864U - Health management system for wearable device - Google Patents

Abstract

The present invention discloses a health management system for a wearable device that is wired to a wearable device that is worn on a tester. The system includes a signal processing unit for receiving and processing the transmitted device. The signal is sensed to generate a physiological signal; the signal quality inspection unit is configured to check the physiological signal of the signal processing unit, so as to exclude the physiological signal that does not meet the test index and filter out the available physiological signal; the availability test unit receives the signal The physiological signal generated by the signal quality inspection unit after inspection, to convert the available physiological signal into physiological data by the availability testing unit, and compare the physiological data with a predefined range of reasonable values to generate an available The physiological index; and the health index calculation unit receives the available physiological index generated by the availability test unit, calculates a health index through the trend change of the available physiological index, and uses the health index to infer the health status of the tester. .

Description

Health management system for wearable devices

This creation is about health data management mechanisms, and more specifically, about a health management system for wearable devices.

In recent years, with the booming of wearable device technology, manufacturers have introduced wearable products such as smart glasses, smart bracelets or smart watches, which provide users with a wide range of applications in daily life. In addition to electronic devices, wearable devices One focus is on health monitoring. The more common applications are step counting, sleep recording, heart rate measurement, blood pressure measurement, fatigue or stress management. The above health information can be transmitted through a three-axis accelerometer or through, for example, an electrocardiogram (ECG). ) or light volume change description (Photoplethysmography, PPG) and other technologies to achieve, in order to record the user's daily life information, and then as a basis for the user's health status.

Although the wearable device provides a more convenient application, there is still room for improvement in health management through such a device. First, although the wearable device is mobile, this is more action-less (or low-mobility) than the conventional medical device. Convenience, but the measurement error of the wearable device is higher than the traditional measurement method. In the measurement by the wearable device, physical activity, light, sweat, dust, etc. will cause measurement errors, and the wear position will follow Moving with physical activity, this It also causes signal error. Secondly, the loading position is also different from the traditional measurement method. For example, the traditional electrocardiograph can be connected to the chest (near the heart), but the loading device is usually located on the wrist or finger, which may cause measurement. The question of whether the signal is available, the above is the problem of sensing signals. In addition, the quality of the commercially available load-carrying devices is uneven. Specifically, the loading device uses the algorithm to obtain the result, and the algorithm is verified, that is, It is said that the application criteria vary from one to another, which results in the same physiological data having different interpretation results on different wearable devices. Moreover, the signal collection and processing also affects the measurement quality. This aspect has nothing to do with the algorithm, and thus the design differences of various products. , the question of whether the data obtained by the wearable device is applicable.

Therefore, based on factors such as hardware limitations of existing wearing devices, signal errors, product differences, etc., there are obvious deficiencies in the health management through the wearable device. If a health management method for the wearing device can be found, in particular, it can be reduced. Due to the external interference of the nature of the wearable device, the use process, and the like, the health information of the combination is obtained, which will become a technical goal that the technical personnel in the art are currently pursuing.

The purpose of this creation is to propose a health management mechanism for the wearer device, in which signal analysis, screening and data integration are used to reduce the problems of wearable device products or external interference, thereby obtaining useful and applicable health. Values, looking forward to improving the wearer's application for better health management.

In order to achieve the above or other objects, the present invention proposes a health management system for a wearable device that is wired to a wearable device worn on a subject, the system comprising: a signal processing unit for receiving and processing The sensing signal transmitted by the wearable device, To generate a physiological signal; the signal quality inspection unit is used for testing the physiological signal of the signal processing unit, so as to exclude the physiological signal that does not meet the test index and filter out the available physiological signal; the availability test unit receives the signal quality test. a physiological signal generated after the unit test, by which the available physiological signal is converted into physiological data, and the physiological data is compared with a predetermined range of values to generate a usable physiological index; The health index calculation unit receives the available physiological index generated by the availability test unit, calculates a health index through a trend change of the available physiological index, and uses the health index to infer the health status of the tester.

In the foregoing system, the test indicator includes a peak, a trough, an average value, a standard deviation, or any combination of the above, and the reasonable range of the value includes a set data threshold or a data oscillation range.

In the foregoing system, the trend change is the relationship between the increase or decrease of the index value and the time, or the magnitude and the number of times of the fluctuation of the index and the time.

In the foregoing system, the health management system for the wearable device further includes a database for storing the health index calculated by the health index calculation unit.

In the foregoing system, the health management system for the wearable device includes a trend change analysis unit for using the health index from the health index calculation unit or the database and the composite data from the outside. The health status of the tester is derived, wherein the composite data includes blood pressure, blood sugar, heart rate or body temperature.

In the foregoing system, the signal processing unit processes the sensing signals transmitted by the wearable device, including noise filtering, normalization processing, or feature value extraction.

As can be seen from the above, the present invention proposes a health management system for a wearable device. The signal verification and the usability check are used to confirm whether the sensing signal obtained by the wearable device is available, wherein the management and verification of the physiological index is not at the wearable device end, but the signal received by the wearable device is returned. To the management system to perform the above-mentioned signal processing, signal quality inspection, availability test and health index calculation. In particular, regarding the health index, the trend change is used as the basis for the health status, instead of using the absolute value as the basis for judgment. This avoids the absolute numerical bias caused by the difference in function, performance or quality of each product. In addition, through the collection and storage of the health index in the health management system, it is possible to achieve the integrity value and change analysis. The signal verification and system management described above can effectively improve the shortcomings of the existing single wearable devices, and can be used in conjunction with the wearable devices of various manufacturers.

1‧‧‧Health Management System for Wearable Devices

10‧‧‧Signal Processing Unit

11‧‧‧Signal quality inspection unit

12‧‧‧ Availability Test Unit

13‧‧‧Health Index Calculation Unit

14‧‧‧Database

15‧‧‧ Trend Change Analysis Unit

2‧‧‧Wearing device

3‧‧‧Composite materials

601~611‧‧‧Process

701~706‧‧‧Process

S31~S34‧‧‧Steps

Please refer to the detailed description of this creation and its drawings for further understanding of the technical content of this creation and its purpose. The related drawings include: Figure 1 is the system for creating a health management system for wearable devices. Architecture diagram.

2 is a system architecture diagram of another embodiment of a health management system for a wearable device.

Figure 3 is a diagram showing the steps of a health management method for a wearable device.

Figures 4A and 4B are diagrams illustrating the verification of signal quality or availability in this creation.

Figure 5 is the internal management of the health management system for the wearable device. Schematic diagram of the work.

Figure 6 is a flow chart of the execution of the signal verification for the health management system.

Figure 7 is a flow chart of the analysis of the trend change in the implementation of the health management system.

The embodiments of the present invention are described below by way of specific embodiments, and those skilled in the art can readily appreciate other advantages and functions of the present invention from the disclosure of the present disclosure.

It is to be understood that the structure, the proportions, the size and the like of the drawings are only used in conjunction with the disclosure of the specification for the understanding and reading of those skilled in the art, and are not intended to limit the implementation of the present invention. The qualifications are not technically meaningful. Any modification of the structure, change of the proportional relationship or adjustment of the size should fall within the creation without affecting the effectiveness and the purpose of the creation. The technical content disclosed can be covered. In the meantime, the terms "upper", "first", "second" and "one" as used in this specification are for convenience only, and are not intended to limit the scope of the creation of the creation. Changes or adjustments in their relative relationship are considered to be within the scope of the creation of the creation of the product without substantial changes.

1 is a system architecture diagram of a health management system for a wearable device of the present invention, and relates to a technique for ensuring the usability of a sense signal generated by a wearable device through signal quality detection and availability detection. As shown, the health management system 1 for a wearable device is tethered to a wearable device 2 worn on the examiner for wearable wear. The health management system 1 includes a signal processing unit 10, a signal quality checking unit 11, an availability checking unit 12, and a health index calculating unit 13.

The signal processing unit 10 is configured to receive and process the sensing signals transmitted by the wearable device 2 to generate a physiological signal. In short, the wearable device 2 is configured to sense the physiological state of the detector to be a sensing signal. After the health management system 1 for the wearable device receives the sensing signal, the signal processing unit 10 processes the sensing signal. To convert it into a physiological signal.

The signal processing unit 10 described above processes the sensing signals transmitted by the wearable device 2, and may include signal processing procedures such as noise filtering, normalization processing, or feature value extraction, but the signal processing is not known in the art. This is the focus of this case, so it will not be detailed here.

The signal quality checking unit 11 is configured to check the physiological signal of the signal processing unit 10, so as to exclude the physiological signals that do not meet the test index and filter out the available physiological signals. The purpose of the signal quality inspection unit 11 is mainly to detect whether the signal is of good quality. As described above, the signal processing unit 10 converts the sensing signal into a physiological signal, but not all physiological signals can be used, such as whether the signal peak, the trough is normal, etc. In order to prevent the inappropriate physiological signal from being used in the subsequent health index judgment, the signal quality checking unit 11 excludes the physiological signals that do not meet the test index through the predetermined test indicators to screen out the available physiological signals.

In an embodiment, the test indicator may include a peak, a trough, an average value, a standard deviation, or any combination of the above, for example, whether a clear peak/trough is stable, and whether the average level is clear. Whether the variation of the drop, the standard deviation can be kept within a certain value, etc., the above-mentioned peaks, troughs, average values or standard deviations of the physiological signals will be the basis for judging the quality of the signal.

The availability verification unit 12 receives the signal produced by the signal quality inspection unit 11 after inspection. The available physiological signal, the availability test unit 12 converts the available physiological signal into physiological data and compares the physiological data with a predefined range of values to produce a usable physiological index. The signal quality checking unit 11 is configured to detect the signal quality, and the availability testing unit 12 is to further check whether the physiological signal is a normal physiological signal, and the purpose is to exclude, for example, an obviously unreasonable value or a value with extreme oscillation, that is, After the signal quality test, whether the calculated physiological value is available, or whether the signal can produce a meaningful physiological index.

In this regard, the availability test unit 12 first converts the available physiological signals into physiological data, and then compares the physiological data with a predetermined range of predetermined values to exclude inappropriate data, thereby obtaining a usable physiological index. In an embodiment, the reasonable range of values may include setting a data threshold or a data oscillation range. For example, if the average heart rate value exceeds or falls below a preset threshold, it cannot be used, for example, a heart rate value greater than 200 or less than 40. It may not be applicable, or the instantaneous heart rate value map may be extremely turbulent and cannot be used.

The health index calculation unit 13 receives the available physiological index generated by the availability test unit 12, calculates a health index through the trend change of the available physiological index, and then uses the health index to estimate the health status of the tester. The health index calculation unit 13 can obtain the available physiological index from the availability test unit 12, and the available physiological index can be continuously transmitted, so the health index calculation unit 13 calculates the health index by the trend change of the available physiological index, that is, It is said that instead of using numerical values as a criterion for judging, the health status of the tester is introduced by continuously changing the value.

It can be seen from the above that this creation does not use the absolute value as the basis for judging the health index, but rather the change in the trend of the physiological index, which will further improve the correctness of the health status of the tester.

The aforementioned trend change is the relationship between the increase or decrease of the index value and the time, or the magnitude and frequency of the fluctuation of the index value and the time. For example, the relationship between the rise/fall of the trend and time can be quantified into an index, so that the user can know his or her health changes, and can immediately adjust the physical and mental condition to prevent it from happening. In an example, at the same time. Under the condition, the slope of the numerical change is used as the basis for judging the health index, which means that the greater the slope, the greater the decrease in the value of the user (such as blood oxygen) detected by the user, and the higher the blood oxygen level. Health risks.

Figure 2 is a block diagram showing the system architecture of another embodiment of the health management system for a wearable device of the present invention. As shown in the figure, the signal processing unit 10, the signal quality checking unit 11, the availability checking unit 12, and the health index calculating unit 13 of the health management system 1 for the wearable device are the same as those described in FIG. As described above, in the present embodiment, the health management system 1 for the wearable device further includes a database 14 and a trend change analysis unit 15.

The database 14 is used to store the health index calculated by the health index calculation unit 13. The database 14 stores the health index generated by the health index calculation unit 13, and when the database 14 accumulates a large number of health indexes, the health management system 1 available for the wearable device can be used as a physiological index through the big data accumulation analysis. The basis for the change in numerical trends.

In addition, in other embodiments, the database 14 can also be used to store the sensing signals from the wearable device 2, so that the sensing signals can also be calculated or referenced by other new health indexes in the future.

The trend change analysis unit 15 is configured to derive the health status of the tester based on the health index from the health index calculation unit 13 or the database 14 and the composite data 3 from the outside. In short, the trend change analysis unit 15 can be from the health index calculation unit 13 or the health index of the database 14 is combined with the external composite data 3 to analyze the trend of the physiological index, which will further estimate the health status of the tester. In addition, the aforementioned composite data may include blood pressure, blood sugar, heart rate or body temperature.

Figure 3 is a diagram showing the steps of the present invention for a health management method for a wearable device. In step S31, the sensing signal from the wearable device is received and processed to generate a physiological signal. In this step, the sensing signal from the wearable device is received and processed to generate a physiological signal, and the sensing signal is generated by the wearable device for physiological data acquisition by the detecting device, but such a signal may exist. The measurement of the disturbed or erroneous situation, so the follow-up should be excluded, so that the physiological data obtained can be used.

In an embodiment, the processing of the sensing signal includes a program such as noise filtering, normalization processing, or feature value extraction.

In step S32, the physiological signal is checked, and the available physiological signals are screened by excluding physiological signals that do not meet the test index. This step illustrates the exclusion of inappropriate physiological signals by means of test indicators, thereby screening for available physiological signals, wherein the test indicators may include peaks, troughs, mean values, standard deviations, or any combination of the above.

In step S33, the available physiological signal is converted into physiological data, and the physiological data is compared with a predetermined range of values to generate a usable physiological index. This step is to filter the available physiological signals from the previous step, and further determine whether the availability is available. Here, a predetermined range of values, such as setting a data threshold or a data oscillation range, for example, cannot be greater than or If it is less than the preset threshold value, or when the numerical oscillation amplitude is large, the value is not referenced to exclude unreasonable physiological data, and then the available physiological index is generated.

In step S34, based on the trend change of the available physiological index to calculate the health The health index, which in turn uses the health index to presume the health status of the tester. This step is to calculate the health index by changing the trend of the physiological index after obtaining the available physiological index. The trend change may be the relationship between the increase or decrease of the index value and the time, or the fluctuation of the index value. The relationship between amplitude and frequency and time, that is, the value of the physiological index is not used as a basis for judging whether it is healthy. Because the single value still has the possibility of misjudgment, this creation proposes to change the trend through, for example, if the heart rate value continues to grow and exceeds The preset value may indicate that the tester's cardiovascular function may be problematic.

In addition, in order to enable the examiner to continuously monitor and manage his or her health status, the method described in the present invention further includes the health status of the tester based on the health index and the composite data from the outside. Specifically, the health index generated in step S34 is continuously stored in the database, and a large number of health indexes can be seen as a change in the health status of the tester. At this time, combined with external composite data such as blood pressure, blood sugar, and heart rate. Or a value such as body temperature, which may be a more accurate value measured by a precision instrument. If the above two types of data are combined, the health status of the tester and the physiological changes or health changes may be more accurately inferred. .

As can be seen from the above, the author examines the health status of the examiner through the original data (ie, the sensing signal of the wearable device), wherein the wearable device provides the original data and the system calculates the health index, including the signal quality check and is available. Through the establishment of the system, the wearable devices of different product categories or models can return the physiological signals they have sensed, and thereby achieve the unified management quality through functional verification, such as verifying the signal quality of the original data and further Calculate the validated health index, so you can achieve personal health management without significantly changing the existing equipment structure or overall structure.

Second, a source of data can correspond to multiple health indicators, that is, quantities A physiological data is measured that can be applied to different health management. For example, the PPG/ECG signal can be used to calculate the heart rate or heart rate variability, and the heart rate variability can be used to estimate the fatigue index or the stress index. By collecting the sensory data of different wearable devices, it will be able to calculate more health indexes, and then connect medical equipment, calculate health management functions and record them as a reference for follow-up health and medical care.

In summary, the biggest benefit of this creation is to provide a value-added service effect, that is, the existing hardware devices do not need to be changed, and the settings of the health check can be adjusted through the system, that is, the software service establishment, update and addition can be completed. The system architecture of the creation, and more importantly, the same or different wearable devices that can correspond to different brands, not limited to specific equipment, will make the data from different manufacturers and operating systems easier to integrate.

The so-called verification of this creation is to test whether the original physiological signal measured by the wearable device can become a meaningful physiological index. Specifically, it can be divided into four stages, including signal processing, signal quality inspection, and availability test. As well as the health index calculation, in particular, the health index does not necessarily correspond to the physiological index. For example, the heart rate variability is a physiological index, but a health index such as fatigue/pressure can be generated. For the signal quality test, the following example can be used to illustrate.

Figures 4A and 4B show schematic diagrams of signal quality or availability tests in this creation. As shown in Figures 4A and 4B, there is a time domain analysis of the PPG signal, where the sampling rate is 100 Hz and the sampling time is 5 seconds. As shown, six distinct waveforms including peaks and troughs can be analyzed. The wave front value will gradually increase, so the average value of each waveform will also increase, but it will not affect the judgment of the waveform. In addition, the waveform will contain noise, but it may be filtered out in the initial signal processing.

As shown in Figure 4A, in the stage of judging the signal quality test, there are peaks and The waveform of the trough is obvious, so there is no signal quality problem, and there are 6 waveforms (ie, heartbeat) in 5 seconds. The heart rate value is 72BPM (Beats per Minute), which falls within a reasonable range, so Through the signal quality test, it can also pass the availability test.

As shown in Fig. 4B, since the waveform containing the peaks and troughs cannot be clearly seen, the signal quality inspection stage may not pass. In addition, the signal value in the figure gradually increases and then slowly decreases. If viewed as a waveform, It means that the heartbeat is 1 time in 5 seconds, and the heart rate value is 12BPM. Therefore, even if the signal quality test is judged, the heart rate value of 12BPM may be regarded as unreasonable in the availability test stage, and it is also impossible to pass the stage test.

Figure 5 illustrates a schematic diagram of the internal operation of the health management system for a wearable device of the present invention. As shown in the figure, the health management system for the wearable device mainly includes two parts, namely signal verification and trend change analysis, in which the original data (the sensing signal of the wearable device) enters the system, and the signal processing is performed first. And quality inspection, and the original data after the aforementioned quality test, but also consider the availability, and the availability can be based on different indices (such as heartbeat, heart rate, blood pressure, etc.) and different availability test criteria, according to which can produce health index For example, the index 1 to index n of different health contents, when the health index is generated according to the trend change, thereby improving the possible misjudgment of a single value (suddenly a too high or too low value), in addition, the index 1~index n Can be sent to a database for storage for subsequent trend analysis.

The index can store index 1~index n, and in the trend change analysis, in addition to obtaining the required health index (index 1~index n) from the database, the composite data can be obtained from the outside, and the composite data may be calculated. Blood pressure, blood sugar, heart rate or body temperature, so the collocation analysis can produce another type of health index (index n+1), which is different from index 1~ index n is the trend change of a period, and index n+1 is the long-term data. Collection and other external data integration, so it can be more accurately judged The health status of the tester. In addition, composite data or trends analysis data can be stored back into the database as a reference for the next trend analysis.

Figure 6 illustrates the flow chart for the execution of the signal verification by the health management system. As shown, in flow 601, the raw material is received. This process refers to the sensing signal sensed by the wearable device connected to the system, that is, the sensing of physiological data.

At process 602, signal processing is performed. The signal processing described in this step may include noise filtering, extracting feature values, etc., to facilitate subsequent signal quality inspection and application.

In the process 603, the signal quality is checked. This process is to test the physiological signal quality, that is, through the physiological signal peak, trough, mean or standard deviation and other test indicators, to exclude inappropriate physiological signals and screen out the available physiological signals.

At flow 604, it is determined whether the signal is available. In this process, if it is determined that the physiological signal is not available, then the process 605 is entered to reply to the signal bad message, and the process proceeds to the process 606 to further perform the availability test.

At flow 606, the verification function is selected. This process is for different health index needs, and may have different signal availability differences. For example, the heart rate index may need to consider whether the value is out of the normal range, but it is used to consider other indexes, which may be the threshold. Therefore, the availability test is used here. Different verifications can be performed according to requirements, so proceeding to process 607, the verification function is performed.

In the process 608, it is determined whether the verification is passed. This process mainly determines whether the available physiological signals are suitable for subsequent analysis. This is called availability, that is, physiological signals with good signal quality but still significant problems in mathematical analysis will be shaved. The reasonable range of values is compared to the pair, and the reasonable range of values may include setting data thresholds or data. Concussion range.

In the process 608, if the verification fails, the process proceeds to the process 609, and the verification failure message is replied. If the verification is successful, the process proceeds to the process 610, and the subsequent process is executed.

At flow 610, a health index is calculated. This process is to continue to calculate the health index, more specifically, to calculate the health index through the trend change of the available physiological index. This creation does not take the absolute value of the physiological index as the standard, but observes the numerical trend of the index. As a reference for the assessment of personal health.

In the process 611, it is determined whether to continue the verification. If yes, the process returns to the process 606. If not, the entire signal verification process is ended.

Figure 7 illustrates a flow chart of the analysis of trends in the implementation of health management systems in this creation. As shown, in process 701, a history of a health index is read, that is, a tester is first retrieved to the sensory data through the wearable device for a period of time and processed and stored in the database. Health index.

At flow 702, a trend change parameter for the health index is taken. This process shows that through the analysis of the health index, the trend of the health index is changed to obtain the trend change parameter.

At process 703, the composite material and its associated history are read. This process description, in addition to the existing health index in the database, will also obtain, for example, a composite data such as the blood pressure, blood sugar, heart rate or body temperature of the tester and the history of the composite data, through the integration of the health index and the composite data, Further as a basis for judging the continuous change of health status.

At flow 704, a trend change parameter for each data is retrieved. This process is to obtain various parameters produced by the process 703.

At flow 705, a trend change analysis is performed to calculate a health index. This process is based on According to the trend change, for example, the magnitude of the value change (slope size) in the same period of time, and then analyze the health index.

At flow 706, the health index is recorded and stored. This process shows that the health index can be stored as a basis for subsequent analysis of the updated data and further analysis.

As can be seen from the above, this creation is a health management system with trend change as the main body. Because the comparison of medical instruments requires high precision, the accuracy of the wear-through device is poor, which leads to a decrease in the reference value of the absolute value, and thus the trend of the numerical value is still changed. Has considerable reference value.

In addition, other trend-changing applications, such as sphygmomanometers, can provide indicators of hypertension/hypotension, that is, wear-through devices track changes in blood pressure/decrease and provide a blood pressure health index by tracking changes in blood pressure taken or Tracking blood pressure changes in adjuvant therapies (such as music, essential oils, etc.) allows users to assess which treatments are more helpful for their blood pressure. For other trend change applications, such as tracking the daily ups and downs of the heart rate, and matching the activity/fatigue/pressure tracking results, the underactivity index is provided. For example, the heart rate tracking results are rarely undulating, indicating the amount of activity. It is low, and in the case of an increase in fatigue/pressure index, an underactivity warning is provided.

In summary, the health management system for the wearable device of the present invention can confirm whether the sensing signal obtained by the wearable device is available by means of signal verification and usability inspection, in particular, the health index generated. The use of trend change as the basis for health status, rather than the use of absolute values as a basis for judgment, can avoid the absolute numerical bias caused by different functions, performance or quality differences of different products. In addition, the collection of health index can be used for numerical system. Through the analysis, this creation can effectively improve the shortcomings of the existing single wearable devices, and combine them with the wearable device products of different manufacturers.

The above embodiments are merely illustrative and are not intended to limit the present invention. Any person skilled in the art can modify and change the above embodiments without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention is defined by the scope of the patent application attached to the present invention, and it should be included in the technical content of the disclosure as long as it does not affect the effect and the purpose of the present invention.

Claims (8)

A health management system for a wearable device, the telecommunications device is connected to a wearable device worn on the examiner, the system comprising: a signal processing unit for receiving and processing the sensing signal transmitted by the wearable device To generate a physiological signal; the signal quality inspection unit is used to test the physiological signal of the signal processing unit, so as to exclude the physiological signal that does not meet the test index and screen out the available physiological signal; the availability test unit receives the signal quality The physiological signal generated by the test unit after the test is performed, so that the available physiological signal is converted into physiological data by the availability test unit, and the physiological data is compared with a predetermined range of reasonable values to generate a usable physiological index; And the health index calculation unit receives the available physiological index generated by the availability test unit, calculates a health index through the trend change of the available physiological index, and uses the health index to infer the health status of the tester. The health management system for a wearable device according to claim 1, wherein the test indicator includes a peak, a trough, an average value, a standard deviation of the physiological signal, or any combination thereof. The health management system for a wearable device according to claim 1, wherein the reasonable range of values includes a set data threshold or a data oscillation range. The health management system for a wearable device according to claim 1, wherein the trend change is a relationship between an increase or decrease in the exponential value and a time, or a magnitude and a time and a time of the fluctuation of the exponential value. Relationship. The health management system for a wearable device according to claim 1 of the patent application, further comprising a database for storing the health index calculated by the health index calculation unit. The health management system for a wearable device according to claim 5, further comprising a trend change analysis unit for using the health index from the health index calculation unit or the database and the composite data from the outside In order to promote the health status of the tester. The health management system for a wearable device according to claim 6, wherein the composite material includes blood pressure, blood sugar, heart rate or body temperature. The health management system for a wearable device according to claim 1, wherein the signal processing unit processes the sensing signal transmitted by the wearable device, including noise filtering, normalization processing, or feature value. take.