TWI799327B - Establishing method and establishing system of personalized physiological status evaluation model, and physiological status evaluation method - Google Patents

Abstract

An establishing method and an establishing system of personalized physiological status evaluation model, and a physiological status evaluation method are provided. The establishing method includes: collecting a plurality of measurement values of a physiological indicator of a user and a plurality of first physiological state exponentials corresponding to the measurement values respectively, and the first physiological state exponentials obtained by the user after self-evaluation from a plurality of physiological state exponentiation levels; and establishing a personalized physiological status evaluation model according to the measurement values and the first physiological state exponentials. The personalized physiological status evaluation model is used to define a plurality of measurement value ranges of the physiological indicator corresponding to the user under the physiological state exponentiation levels respectively.

Description

Method and system for establishing a personalized physiological state assessment model, and physiological state assessment method

The present invention relates to a method and system for establishing an evaluation model, in particular to a method and system for establishing a personalized physiological state evaluation model, and a physiological state evaluation method using the personalized physiological state evaluation model established by the establishment method.

In the traditional physiological state assessment method, the doctor can according to the measurement value of a physiological index (such as heartbeat, blood pressure or heart rate variability, etc.) of the user falls into which physiological state index level defined in the big data database The user's physiological state is evaluated within the measured value range. However, affected by factors such as race, occupation, gender, age, etc., the range of measurement values defined by the big data database cannot be applied to everyone. For example, the blood pressure of Asians may generally be higher than that of Europeans, and As for easy assessment errors, delaying medical treatment or inappropriate treatment. In addition, in practice, there are often not enough doctors who can define multiple measurement value ranges of physiological indicators corresponding to multiple physiological state index levels for each individual.

The technical problem to be solved by the present invention is to provide a method and a system for establishing a personalized physiological state assessment model and a physiological state assessment method for the deficiencies of the prior art, which can define a number of physiological state index levels for each individual. A plurality of measurement value ranges of corresponding physiological indexes respectively.

In order to solve the above-mentioned technical problems, one of the technical solutions adopted by the present invention is to provide a method for establishing a personalized physiological state assessment model, which includes: collecting multiple measurement values of a physiological index of the user and these measurement values Corresponding to multiple first physiological state indexes, and these first physiological state indexes are obtained by the user after self-assessment from multiple physiological state index levels; and based on these measured values and these first physiological state indexes, establish Personalized Physiological State Assessment Model. The individualized physiological state evaluation model is used to define multiple measurement value ranges of the physiological index respectively corresponding to the user's physiological state index levels. The personalized physiological state evaluation model is also used to take an instant measurement value of the physiological index as an input, and evaluate a second physiological state index corresponding to the instant measurement value according to the range of these measurement values as an output.

In order to solve the above technical problems, another technical solution adopted by the present invention is to provide a system for establishing a personalized physiological state assessment model, which includes a cloud device and a computing device. The cloud device is used to store a plurality of measured values of a physiological index of the user and a plurality of first physiological state indexes corresponding to these measured values, and these first physiological state indexes are determined by the user from the plurality of physiological state indexes obtained after a self-assessment at the level. Computing devices include memory, communication circuitry, and processing circuitry. The communication circuit is used for communicating with the cloud device to receive the measured values and the first physiological state indexes. The processing circuit is configured to establish a personalized physiological state assessment model according to the measured values and the first physiological state indices.

The individualized physiological state evaluation model is used to define multiple measurement value ranges of the physiological index respectively corresponding to the user's physiological state index levels. The personalized physiological state evaluation model is also used to take an instant measurement value of the physiological index as an input, and evaluate a second physiological state index corresponding to the instant measurement value according to the range of these measurement values as an output.

In order to solve the above-mentioned technical problems, another technical solution adopted by the present invention is to provide a physiological state assessment method, which includes: applying the aforementioned establishment method to establish a personalized physiological state assessment model, and through the personalized physiological state assessment model The model evaluates the second physiological state index corresponding to the real-time measurement value of the physiological index of the user; and in response to judging that the second physiological state index reaches a dangerous level zone, sends out a warning signal to notify the preset medical institution to effectively Help users get immediate medical treatment.

In order to further understand the features and technical content of the present invention, please refer to the following detailed description and drawings related to the present invention. However, the provided drawings are only for reference and description, and are not intended to limit the present invention.

The implementation of the present invention is illustrated through specific specific examples below, and those skilled in the art can understand the advantages and effects of the present invention from the content provided in this specification. The present invention can be implemented or applied through other different specific embodiments, and various modifications and changes can be made to the details in this specification based on different viewpoints and applications without departing from the concept of the present invention. In addition, the drawings of the present invention are only for simple illustration, and are not drawn according to the actual size, which is stated in advance. The following embodiments will further describe the relevant technical content of the present invention in detail, but the provided content is not intended to limit the protection scope of the present invention.

Please refer to FIG. 1 . FIG. 1 is a flowchart of a method for establishing a personalized physiological state assessment model provided by the first embodiment of the present invention. As shown in FIG. 1 , the method for establishing a personalized physiological state assessment model according to an embodiment of the present invention may include the following steps S110-S120.

Step S110: Collect a plurality of measured values of a physiological index of the user and a plurality of first physiological state indexes corresponding to these measured values, and these first physiological state indexes are determined by the user from a plurality of physiological state index levels obtained after self-assessment. Next, Step S120: Establish a personalized physiological state evaluation model according to the measured values and the first physiological state indices.

For the convenience of the following description, in this embodiment, the first physiological state index mentioned in step S110 may be, for example, a pressure index, and the physiological index may be, for example, heart rate variability (Heart Rate Variability, HRV), and the measured value of HRV Corresponds to the pressure index, but the present invention is not limited thereto. In addition, in this embodiment, it may be assumed that ten measurement values of the user's HRV are collected, and the first pressure index corresponding to the ten measurement values can be selected by the user from five pressure index levels (for example, stress Index: 1 to 5) obtained after self-assessment.

Please refer to Table 1 and Table 2 together. Table 1 is the HRV measurement value range of the five stress index levels defined by the big data database, and Table 2 is the first stress index self-assessed by the user and through the big data Comparison table of database-assessed stress indices. It should be understood that a higher stress index can easily lead to neurasthenia. In other words, physiological states with a stress index of 1 and 2 are more relaxed and have a younger overall physiology, but those with a stress index of 4 and 5 are more fatigued and have an older overall physiology. In addition, as shown in Table 2, the first pressure index corresponding to the first measured value of HRV (5.25) that users can self-assess is 3, but the pressure index evaluated through the big data database is 2, so that By analogy, the first stress index corresponding to the tenth measured value of HRV (9.55) that the user can self-assess is 4, but the stress index evaluated through the big data database is 3. [Table 1] pressure index HRV measurement value (m) range 1 0<m≤3 2 3<m≤6.5 3 6.5<m≤10 4 10<m≤15 5 15<m≤20 [Table 2] project Measured value of HRV The first stress index self-assessed by users Stress index assessed through big data database error 1 5.25 3 2 1 2 11.55 5 4 1 3 6.35 3 2 1 4 2.51 2 1 1 5 4.78 3 2 1 6 8.54 4 3 1 7 7.46 3 3 0 8 1.24 2 1 1 9 1.96 2 1 1 10 9.55 4 3 1

Therefore, the HRV measurement value range of the five stress index levels defined by the big data database cannot be applied to this user, and it is easy to make evaluation errors that cause delays in medical treatment or inappropriate treatment.

Take item 10 in Table 1 as an example. At this time, the user self-assessed the first stress index is 4, which means that the user already feels tired and weak, so it should be treated as soon as possible to avoid neurasthenia. The stress index evaluated by the data database is 3, which makes the doctor think that the overall physiological function of the user is normal, which causes delay in seeking medical treatment.

On the other hand, taking item 1 of Table 1 as an example, since the stress index evaluated by the big data database is 2, the doctor will think that the user can take some methylphenidate to activate the nerves, but at this time the user self-evaluates The first stress index of the drug is 3, which means that the overall physiological function of the user is normal. Therefore, taking methylphenidate again (that is, improper treatment) may cause the user's autonomic nervous system to become abnormal.

Therefore, in order to solve the above-mentioned problems, the personalized physiological state evaluation model of the present embodiment is used to define a plurality of measurement value ranges of the physiological index corresponding to the user at a plurality of physiological state index levels. In addition, the personalized physiological state evaluation model can also be used to take a real-time measured value of the physiological index as an input, and evaluate a second physiological state index corresponding to the real-time measured value according to the range of these measured values as an output.

Specifically, in step S120, the measured values and the first physiological state indices can be used to train a machine learning model to establish a personalized physiological state evaluation model. For example, after using the ten measured values of HRV in Table 1 and the first pressure indices corresponding to the ten measured values to train the machine learning model, this embodiment can adjust the big data database for the user The range of measured values of HRV for the five stress index levels defined.

Please refer to Table 3 and Table 4 together. Table 3 is the measurement value range of HRV under the five pressure index levels defined by the personalized physiological state assessment model of this embodiment, and Table 4 is self-assessed by the user. A comparison table of a stress index and a second stress index assessed by a personalized physiological state assessment model. As shown in Table 4, when an instant measurement of HRV (for example, 6.27 in item 11) is input into the Personalized Physiological State Assessment Model, the Personalized Physiological State Assessment Model can be evaluated according to the range of measurement values in Table 3 The second pressure index corresponding to the instant measurement value is 3. [table 3] pressure index HRV measurement value (m) range 1 0<m≤1 2 1<m≤3.9 3 3.9<m≤7.6 4 7.6<m≤11.2 5 11.2<m≤14.8 [Table 4] project Measured value of HRV The first stress index self-assessed by users Second stress index assessed by the Personalized Physiological State Assessment Model error 1 5.25 3 - - 2 11.55 5 - - 3 6.35 3 - - 4 2.51 2 - - 5 4.78 3 - - 6 8.54 4 - - 7 7.46 3 - - 8 1.24 2 - - 9 1.96 2 - - 10 9.55 4 - - 11 6.27 3 3 0

In other words, using these measured values and these first stress indices to train the machine learning model, so that the second stress index assessed by the personalized physiological state assessment model is as close as possible to the first stress index self-assessed by the user, Furthermore, it can truly reflect the physiological state of the user, and help doctors accurately judge whether the user needs to receive treatment. In addition, since training a machine learning model to establish a personalized physiological state assessment model requires a large amount of historical data (such as the measured values of items 1-10 in Table 2 and the first physiological state indices), this embodiment can S120 is re-executed after the historical data is increased, so as to redefine the ranges of multiple measurement values corresponding to the user's multiple physiological state index levels, that is, to realize the dynamic adjustment of the personalized physiological state evaluation model.

It should be noted that in this embodiment, multiple measurement values of the user's HRV can be obtained under multiple situations, multiple modes, or multiple time points, and the so-called self-evaluation by the user obtains these first The physiological state index may mean that the user classifies multiple physiological states under these situations, these modes, or these time points. Therefore, please refer to FIG. 2 together. FIG. 2 is a flow chart of collecting a plurality of measured values and a plurality of first physiological state indices according to an embodiment of the present invention. As shown in FIG. 2, step S110 may include steps S111-S113.

Step S111 : Obtain a plurality of measurement values of a physiological index of the user under multiple situations, multiple modes or multiple time points through a physiological index measuring device. Next, step S112: the user classifies the multiple physiological states under these situations, these modes, or these time points, so as to obtain the first physiological state indices corresponding to the measurement values. For example, the user can measure HRV in the morning and evening every day, and classify the physiological state in the morning and evening every day, that is, take the initiative to measure and classify stress regularly. Next, step S113: storing the measured values and the first physiological state indices in a cloud device.

On the other hand, in addition to using these measured values and these first physiological state indexes to train the machine learning model to establish a personalized physiological state assessment model, please refer to FIG. And a flow chart of establishing a personalized physiological state evaluation model with these first physiological state indexes. As shown in FIG. 3 , step S120 may include steps S121-S125. Step S121: According to the measured values and the first physiological state indices, calculate the average values of the measured values and the standard deviations of the measured values respectively corresponding to the levels of the physiological state indices. Next, step S122: According to the average value of these measured values and the standard deviation of these measured values, obtain the multiple measured value ranges of the physiological indicators corresponding to the user's physiological state index levels respectively, so as to establish a personalized physiological state Evaluate the model.

Taking Table 2 as an example, the measured values corresponding to the first pressure index of 2 are 2.51, 1.24 and 1.96, then the average value and standard deviation of the measured values corresponding to the pressure index level of 2 are 2.51, 1.24 and 1.96 The average value and standard deviation, and the measured values corresponding to the first pressure index of 3 are 5.25, 6.35, 4.78 and 7.46, then the average value and standard deviation of the measured values of the pressure index level 3 are 5.25, 6.35 , mean and standard deviation of 4.78 and 7.46. Therefore, in this embodiment, the average value of the measured value and the standard deviation of the measured value corresponding to each pressure index level can be calculated.

Secondly, in this embodiment, the HRV measurement value (m) range corresponding to the i-th pressure index level can be set as Xi_1<m≤Xi_2, that is, between greater than Xi_1 and less than or equal to Xi_2, where Xi_1 is The result of the average value of the measured value corresponding to the i-th pressure index level minus the standard deviation of the corresponding measured value, and Xi_2 is the average value of the measured value corresponding to the i-th pressure index level plus the corresponding standard deviation of the measured value the result of. i is an integer from 1 to N, and N is the total number of pressure index levels. For example, five pressure index levels in this embodiment mean that N is 5.

It should be understood that if the result of the average value of the measurement value corresponding to the previous pressure index level plus the standard deviation of the corresponding measurement value is not equal to the average value of the measurement value corresponding to the next pressure index level minus the corresponding measurement value As a result of the standard deviation, there will be a value range where the pressure index cannot be evaluated between the measurement value ranges corresponding to the two pressure index levels. Therefore, in step S122, the standard deviation of these measured values can also be adjusted so that the result of adding the average value of the measured value corresponding to the previous pressure index level to the corresponding standard deviation of the measured value is equal to the amount corresponding to the latter pressure index level The result of subtracting the corresponding standard deviation of the measured value from the mean value of the measured value.

It should also be understood that the average value and standard deviation of the measured value will be affected by historical data, and may obtain an unsuitable range of measured values, that is, the second stress index evaluated by the personalized physiological state assessment model may also be Not equal to the first stress index self-assessed by the user. Therefore, in order to improve the evaluation accuracy of the personalized physiological state evaluation model, after step S122, step S123: determine whether the evaluation accuracy of the personalized physiological state evaluation model reaches an accuracy standard. If yes, it means that the currently established personalized physiological state evaluation model has high evaluation accuracy, so it can go to step S124: store the personalized physiological state evaluation model in the cloud device. If not, it means that the currently established personalized physiological state evaluation model does not have high evaluation accuracy, so go to step S125: adjust the standard deviation of these measurement values. Then, after step S125, it may return to step S122.

In other words, in response to judging that the assessment accuracy of the personalized physiological state assessment model does not meet an accuracy standard, this embodiment adjusts the standard deviation of these measurement values, and returns the average value of these measurement values and the The standard deviation is a step of obtaining multiple measurement value ranges of physiological indicators corresponding to the user's physiological state index levels respectively. In practice, this embodiment can form a test set from historical data, and use the test set to obtain the assessment accuracy of the personalized physiological state assessment model. Since the accuracy rate of the evaluation model is obtained by using the test set is a technical means known to those skilled in the art, the details thereof will not be repeated here.

Similarly, in this embodiment, steps S121-S125 may be re-executed after the historical data is added. In addition, when the collected measurement values do not correspond to a certain pressure index level, this embodiment can use interpolation or fitting to find out the corresponding pressure index level according to the range of measurement values corresponding to other pressure index levels. range of measured values. In a word, FIG. 3 is only an implementation manner of establishing a personalized physiological state assessment model based on these measured values and these first physiological state indexes, but the present invention is not limited thereto.

Incidentally, HRV can also be correlated with average heart rate, heart rate variability total energy, cardiac function index, cardiac load index, long-term sympathetic nerve activity index, long-term parasympathetic nerve activity index, sympathetic and parasympathetic nerve balance index, mood index, etc. Therefore, these physiological indicators mentioned above can form a set of physiological indicators related to HRV, and the personalized physiological state assessment model of this embodiment can be used to form a radar of the set of physiological indicators of the user at these physiological state index levels. picture.

On the other hand, please refer to FIG. 4 , which is a functional block diagram of a system for establishing a personalized physiological state assessment model provided by an embodiment of the present invention. As shown in FIG. 4 , the system 1 for establishing a personalized physiological state assessment model 146 may include a cloud device 12 and a computing device 14 . The cloud device 12 is used for storing a plurality of measured values of a physiological index (such as HRV) of the user and a plurality of first physiological state indices corresponding to the measured values.

The computing device 14 includes a memory 140 , a communication circuit 142 and a processing circuit 144 . The communication circuit 142 is used to communicate with the cloud device 12 , receive the measured values and the first physiological state indexes, and store the measured values and the first physiological state indexes in the memory 140 . In addition, the processing circuit 144 is configured to establish a personalized physiological state assessment model 146 according to the measured values and the first physiological state indices.

The communication circuit 142 and the processing circuit 144 can be implemented by hardware and software and/or firmware, but the present invention does not limit the specific implementation of the communication circuit 142 and the processing circuit 144 . In addition, the cloud device 12 and the computing device 14 can be integrated or set separately, but the present invention is not limited thereto. As shown in FIG. 4 , the establishment system 1 may further include a physiological index measurement device 10 . The physiological indicator measurement device 10 is used to obtain multiple measurement values of the user's physiological indicators under multiple situations, multiple modes, or multiple time points, and the user separately evaluates these situations, these modes, or these time points. The multiple physiological states under the click are classified to obtain the first physiological state indices corresponding to the measured values, and then the measured values and the first physiological state indices are stored in the cloud device 12 .

It should be noted that the computing device 14 can also communicate with the physiological index measuring device 10 through the communication circuit 142 to directly receive the measured values and the first physiological state indexes from the physiological index measuring device 10 . In addition, in one embodiment, the processing circuit 144 is configured to use the measured values and the first physiological state indices to train a machine learning model to establish the personalized physiological state assessment model 146 .

In another embodiment, the processing circuit 144 is configured to calculate a plurality of average values and a plurality of standard deviations of measurement values respectively corresponding to these physiological state index levels according to these measurement values and the first physiological state indexes , and according to the average value of these measured values and the standard deviation of these measured values, a plurality of measured value ranges of the corresponding physiological indicators of the user at these physiological state index levels are obtained, so as to establish a personalized physiological state evaluation model 146 . In addition, the processing circuit 144 is further configured to recreate the personalized physiological state assessment model 146 based on the collected measured values and the first physiological state indexes in response to the increase in the number of the collected measured values and the first physiological state indexes, so as to A plurality of measurement value ranges respectively corresponding to the user under a plurality of physiological state index levels are retrieved, and the computing device 14 can also store the personalized physiological state evaluation model 146 in the cloud device 12 . Since the relevant details are the same as those of the foregoing embodiments, no more details are given here.

Finally, please refer to FIG. 5 , which is a flowchart of a physiological state assessment method provided by an embodiment of the present invention. As shown in FIG. 5 , the physiological state assessment method of this embodiment may include steps S510-S550. Step S510: Establish a personalized physiological state assessment model, that is, apply the establishment method of the foregoing embodiment to establish a personalized physiological state assessment model. Next, step S520: Evaluate the second physiological state index corresponding to the real-time measurement value of the user's physiological index through the personalized physiological state evaluation model. Next, step S530: determine whether the second physiological state index reaches a dangerous level range (eg, the stress index in the foregoing embodiment: 4-5). If yes, the physiological state assessment method may enter step S540: send out a warning signal to notify the preset medical institution, so as to help the user obtain immediate treatment. If not, the physiological state assessment method may enter step S550 to end.

To sum up, one of the beneficial effects of the present invention is that multiple measurement value ranges of physiological indicators corresponding to multiple physiological state index levels can be defined for each person. In addition, the second physiological state index evaluated by the personalized physiological state evaluation model can be equal to the first physiological state index self-assessed by the user as far as possible, so as to more truly reflect the physiological state of the user and help doctors to Accurately determine whether the user needs to receive treatment, so as to avoid delays in medical treatment or inappropriate treatment due to evaluation errors. Moreover, users can know whether their physiological state has improved or deteriorated based on the long-term recorded physiological state index, and adjust their daily routine, eating habits, and sleep patterns.

The content provided above is only a preferred feasible embodiment of the present invention, and does not therefore limit the scope of the patent application of the present invention, so all equivalent technical changes made by using the description and drawings of the present invention are included in the application of the present invention within the scope of the patent.

S110~S120, S111~S113, S121~S125, S510~S550: steps 1: Build a system 10: Physiological index measurement device 12: Cloud device 14: Computing device 140: Memory 142: Communication circuit 144: Processing circuit 146: Personalized Physiological State Assessment Model

Fig. 1 is a flowchart of a method for establishing a personalized physiological state assessment model provided by the first embodiment of the present invention.

FIG. 2 is a flow chart of collecting a plurality of measured values and a plurality of first physiological state indices according to an embodiment of the present invention.

FIG. 3 is a flow chart of establishing a personalized physiological state assessment model according to the measured values and the first physiological state indexes according to an embodiment of the present invention.

Fig. 4 is a functional block diagram of a system for establishing a personalized physiological state assessment model provided by an embodiment of the present invention.

Fig. 5 is a flowchart of a physiological state assessment method provided by an embodiment of the present invention.

S110~S120: steps

Claims (11)

A method for establishing a personalized physiological state assessment model, comprising: collecting a plurality of measured values of a physiological index of a user and a plurality of first physiological state indexes respectively corresponding to the measured values, and the first physiological state indexes The state index is obtained by the user after self-assessment from multiple physiological state index levels; and the personalized physiological state evaluation model is established according to the measured values and the first physiological state indexes; wherein, the personalized The physiological state evaluation model is used to define the multiple measurement value ranges of the physiological index corresponding to the physiological state index levels of the user; wherein, the personalized physiological state evaluation model is also used to use the physiological index A real-time measured value is used as an input, and a second physiological state index corresponding to the real-time measured value is evaluated according to the range of the measured values as an output. The establishment method as described in claim item 1, wherein the step of collecting the measured values of the physiological index of the user and the first physiological state indexes respectively corresponding to the measured values includes: using a physiological index The measurement device obtains the measured values of the physiological index of the user under multiple situations, multiple modes or multiple time points, and the user separately evaluates the situations, modes or Classifying multiple physiological states at time points to obtain the first physiological state indices corresponding to the measured values; and storing the measured values and the first physiological state indices in a cloud device. The establishment method as described in claim 1, wherein, according to the measured values and the The step of establishing the personalized physiological state evaluation model with the first physiological state indexes includes: calculating the average values of the multiple measured values corresponding to the levels of the physiological state indexes according to the measured values and the first physiological state indexes and a plurality of standard deviations of the measured values; according to the average value of the measured values and the standard deviation of the measured values, the measured values of the physiological indicators respectively corresponding to the user at the levels of the physiological state index are obtained range to establish the personalized physiological state evaluation model; and in response to judging that an evaluation accuracy rate of the personalized physiological state evaluation model does not meet an accuracy rate standard, adjust the standard deviation of these measurement values, and return the The average value of the measured values and the standard deviation of the measured values are used to obtain the ranges of the measured values of the physiological indicators corresponding to the user's physiological state index levels. The establishment method as described in claim item 3, wherein, according to the average value of the measured values and the standard deviation of the measured values, the corresponding physiological indicators of the user at the levels of the physiological state index are obtained The step of measuring the value range includes: setting the measurement value range of the physiological index corresponding to the i-th physiological state index level to be between greater than Xi_1 and less than or equal to Xi_2, Xi_1 being the i-th physiological state index level The corresponding average value of the measured value minus the corresponding standard deviation of the measured value, and Xi_2 is the average value of the measured value corresponding to the i-th physiological state index level plus the corresponding standard deviation of the measured value , where i is an integer from 1 to N, and N is the total number of these physiological state index levels; and the standard deviation of these measurement values is adjusted so that the average value of the measurement value corresponding to the previous physiological state index level plus The result corresponding to the standard deviation of the measured value is equal to The result of subtracting the corresponding standard deviation of the measured value from the mean value of the measured value corresponding to the latter physiological state index level. The establishment method according to claim 3, wherein the step of establishing the personalized physiological state evaluation model according to the measured values and the first physiological state indexes can also respond to the collected measured values and the The method is re-executed by increasing the number of the first physiological state indices, so as to regain the measurement value ranges of the physiological indicators corresponding to the user's physiological state index levels. A system for establishing a personalized physiological state evaluation model, comprising: a cloud device for storing a plurality of measured values of a physiological index of a user and a plurality of first physiological state indices corresponding to the measured values, And these measurement values are obtained by the user after self-assessment from multiple physiological state index levels; and a computing device, including: a memory; a communication circuit, used to communicate with the cloud device and receive the These measured values and these first physiological state indices; and a processing circuit configured to establish the personalized physiological state assessment model according to these measured values and these first physiological state indices; wherein, the personalized The physiological state evaluation model is used to define the multiple measurement value ranges of the physiological index corresponding to the physiological state index levels of the user; wherein, the personalized physiological state evaluation model is also used to use the physiological index A real-time measured value is used as an input, and a second physiological state index corresponding to the real-time measured value is evaluated according to the range of the measured values as an output. The establishment system as described in Claim 6, further comprising: a physiological index measurement device, used to obtain the measurements of the user's physiological index under multiple situations, multiple modes, or multiple time points values, and the user classifies the situations, the modes, or the multiple physiological states at the time points, so as to obtain the first physiological state indices corresponding to the measured values; wherein the The physiological index measuring device is also used for storing the measured values and the first physiological state indexes in the cloud device. The establishment system as claimed in claim 6, wherein the processing circuit is configured to further re-based the measured values and the Establishing the personalized physiological state assessment model based on the first physiological state indexes, so as to retrieve the measured value ranges of the physiological indexes respectively corresponding to the user's physiological state index levels. The establishment system according to claim 6, wherein the physiological index is heart rate variability, and the first physiological state index or the second physiological state index is a stress index. The establishment system as described in Claim 9, wherein the personalized physiological state evaluation model is also used to form a radar chart of a physiological index set of the user at the level of the physiological state index, and the physiological index set is associated with in the heart rate variability. A method for assessing a physiological state, comprising: applying the establishing method as described in Claim 1 to establish the personalized physiological state evaluating the model, and evaluating the second physiological state index corresponding to the real-time measurement value of the physiological index of the user through the personalized physiological state evaluation model; and in response to judging that the second physiological state index reaches a dangerous level zone In the paragraph, a warning signal is sent to notify a preset medical institution, so as to help the user obtain immediate medical treatment.

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