Psychological state monitoring and evaluating system based on smart bracelet

Abstract

The invention relates to the technical field of health monitoring, and discloses a psychological state monitoring and evaluation system based on a smart bracelet, which comprises a smart bracelet main body, a cloud server and a third-party mobile device which are mutually connected, and the smart bracelet main body comprises a data acquisition module, an emotion recognition module, a physiological data analysis module and an intervention module. The data acquisition module acquires physiological data of a user and uploads the physiological data to the cloud server for analysis and processing, the emotion recognition module is matched with the intervention module, the emotion recognition module is used for recognizing the emotion of the user in real time, and the data acquisition module acquires the physiological data through a built-in A / D converter and transmits the physiological data to the emotion recognition module through a network; the emotion recognition module comprises a physiological data analysis unit, a physiological signal processing unit and a third-party emotion recognition algorithm unit, and the physiological data analysis module calculates a physiological abnormality score Fz, a physiological pressure comprehensive index Rz, an emotion upper region value Er and an emotion lower region value Ei.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and in particular to a psychological state monitoring and evaluation system based on a smart bracelet. Background Art

[0002] With the improvement of living standards and the increase of work pressure, more and more people are facing mental health problems. However, the traditional diagnosis and treatment evaluation of mental illnesses mostly rely on subjective methods and lack objective measurement tools, which makes it difficult to identify early emotional disorders. Therefore, it is necessary to develop an effective and convenient system to evaluate mental state. Summary of the invention

[0003] 1. Technical issues to be solved

[0004] In view of the shortcomings of the existing technology, the present invention provides a psychological state monitoring and evaluation system based on a smart bracelet, which has the advantages of effectively and conveniently evaluating psychology, and solves the problem that traditional technology lacks objective measurement tools, resulting in difficulty in identifying early emotional disorders.

[0005] (II) Technical solution

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: A psychological state monitoring and evaluation system based on a smart bracelet, comprising a smart bracelet body, a cloud server and a third-party mobile device connected to each other;

[0007] The smart bracelet body includes a data acquisition module, an emotion recognition module, a physiological data analysis module and an intervention module;

[0008] The data acquisition module collects the user's physiological data and uploads it to the cloud server for analysis and processing, and the emotion recognition module cooperates with the intervention module through the network. The emotion recognition module is used to recognize the user's emotions in real time. The data acquisition module collects physiological data through a built-in A / D converter and transmits the physiological data to the emotion recognition module through the network for data analysis, processing and recognition;

[0009] The emotion recognition module includes a physiological data analysis unit, a physiological signal processing unit and a third-party emotion recognition algorithm unit. The physiological data analysis unit analyzes physiological data through text emotion, the physiological signal processing unit recognizes physiological signal processing data through voice emotion, and the third-party emotion recognition algorithm unit recognizes third-party emotion data through physiological emotion. The physiological data analysis unit, the physiological signal processing unit and the third-party emotion recognition algorithm unit are connected to the physiological data analysis module through a network;

[0010] The physiological data analysis module is used to parse the physiological data collected by the bracelet into digital signals that can be processed by the algorithm. The physiological data analysis module includes a physiological data calculation unit, a physiological signal calculation unit and a third-party emotion recognition algorithm unit. The physiological data calculation unit calculates the physiological abnormality score Fz according to the physiological data, the physiological signal calculation unit calculates the physiological stress comprehensive index Rz according to the physiological signal processing data, and the third-party emotion recognition algorithm unit calculates the emotion upper zone value Er and the lower zone value Ei according to the third-party emotion data. The physiological data calculation unit, the physiological signal calculation unit and the third-party emotion recognition algorithm unit are connected to the intervention module through a network.

[0011] Preferably, the data acquisition module mainly acquires: physiological data including heart rate, blood oxygen, galvanic skin response, user voice and environmental voice data.

[0012] Preferably, the physiological data analysis unit numbers the heart rate variability data, the skin electrode activity data and the heart rate data according to the physiological data characteristics, and the heart rate variability data, the skin electrode activity data and the heart rate data are numbered X1, X2 and X3 respectively.

[0013] Preferably, the physiological data calculation unit calculates the physiological abnormality score Fz according to the physiological data, and the calculation formula is:

[0014] Fz=a*X1+b*X2+c*X3

[0015] In the formula, Fz represents the physiological abnormality score, X1, X2, and X3 represent the heart rate variability data, the skin electrode activity data, and the heart rate data, respectively, and a, b, and c represent the weighted coefficients of the heart rate variability data, the skin electrode activity data, and the heart rate data in the physiological abnormality score, respectively.

[0016] Preferably, the physiological signal processing unit numbers the resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain waves, blood pressure and blood sugar under the physiological stress state according to the physiological signal processing data characteristics, and the resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain waves, blood pressure and blood sugar under the physiological stress state are numbered Y1, Y2, Y3, Y4, Y5, Y6, Y7, Y8, respectively.

[0017] Preferably, the physiological signal calculation unit calculates the physiological stress comprehensive index Rz according to the physiological signal processing data, and the calculation formula is:

[0018]

[0019] In the formula, Rz represents the comprehensive index of physiological stress, Y1, Y2, Y3, Y4, Y5, Y6, Y7, and Y8 represent the resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain wave, blood pressure, and blood sugar under physiological stress, respectively. i It represents an indicator under physiological stress state. e1, e2, e3, e4, e5, e6, e7, and e8 respectively represent the weighted coefficients of resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain wave, blood pressure, and blood sugar in the comprehensive physiological stress index under physiological stress state. i It represents the weighting coefficient of a certain indicator under physiological stress state.

[0020] Preferably, the third-party emotion recognition algorithm unit numbers the emotional word strength, degree adverb weight and negation word weight in the emotional fluctuation state of the smart bracelet according to the third-party emotion data characteristics, and the emotional word strength in the emotional fluctuation state of the smart bracelet is numbered as T1, T2, T3, ... T n The weights of the degree adverbs in the emotional fluctuation state of the smart bracelet are numbered as v1, v2, v3, ...v n The weight numbers of negative words in the emotional fluctuation state of the smart bracelet are k1, k2, k3, ...k n .

[0021] Preferably, the third-party emotion recognition algorithm unit calculates the emotion upper zone value Er according to the third-party emotion data, and the calculation formula is:

[0022]

[0023] In the formula, Er represents the upper emotional zone value, T1, T2, T3, ...T n Indicates the intensity of emotional words in the emotional fluctuation state of the smart bracelet, T i Indicates the intensity of a certain level of emotional words in the emotional fluctuation state of the smart bracelet, v1, v2, v3, ...v n Indicates the weight of degree adverbs in the emotional ups and downs of the smart bracelet, v i Indicates the weight of a degree adverb in the emotional ups and downs of the smart bracelet, k1, k2, k3, ...k n represents the weight of negative words in the emotional fluctuation state of the smart bracelet, k i Indicates the weight of a negative word in the emotional fluctuation state of the smart bracelet.

[0024] Preferably, the third-party emotion recognition algorithm unit calculates the emotion lower zone value Ei according to the third-party emotion data, and the calculation formula is:

[0025]

[0026] In the formula, Ei represents the lower range of emotion, T1, T2, T3, ...T n Indicates the intensity of emotional words in the emotional fluctuation state of the smart bracelet, T i Indicates the intensity of a certain level of emotional words in the emotional fluctuation state of the smart bracelet, v1, v2, v3, ...v n Indicates the weight of degree adverbs in the emotional ups and downs of the smart bracelet, v i Indicates the weight of a degree adverb in the emotional ups and downs of the smart bracelet, k1, k2, k3, ...k n represents the weight of negative words in the emotional fluctuation state of the smart bracelet, k i Indicates the weight of a negative word in the emotional fluctuation state of the smart bracelet.

[0027] Preferably, the intervention module generates personalized intervention suggestions based on emotion recognition and in combination with the physiological abnormality score Fz, the comprehensive physiological stress index Rz, and the upper and lower emotional zone values ​​Er and Ei. At the same time, the intervention module is used to recommend specific intervention suggestions and suggestion status to the user.

[0028] Compared with the prior art, the present invention provides a psychological state monitoring and evaluation system based on a smart bracelet, which has the following beneficial effects:

[0029] 1. The present invention can detect user data in real time, analyze and infer the user's emotional state, establish a model based on an intelligent algorithm, predict the user's psychological state, and more comprehensively evaluate the user's mental health status. It can also provide personalized intervention suggestions, so that users can better manage their emotions and improve their mental health level.

[0030] 2. The present invention calculates the physiological abnormality score Fz by numbering and weighting. The smart bracelet device can monitor and evaluate the user's health status in real time and effectively, which helps the user to pay attention to his or her physiological state in real time. At the same time, the smart bracelet can also provide an emergency warning when the heart rate variability data, skin electrodermal activity data and heart rate data are abnormal, so as to make emergency treatment in advance to prevent health problems related to heart rate and skin. The promotion and application of the present invention is conducive to promoting the development of personal health management and enhancing people's awareness of and management ability of their own health. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the structure of the present invention; DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.

[0033] See also Figure 1 , a mental state monitoring and evaluation system based on a smart bracelet, including an interconnected smart bracelet body, a cloud server, and a third-party mobile device;

[0034] The smart bracelet body includes a data acquisition module, an emotion recognition module, a physiological data analysis module, and an intervention module;

[0035] The data acquisition module collects the user's physiological data and uploads it to the cloud server for analysis and processing. The emotion recognition module cooperates with the intervention module through the network. The emotion recognition module is used to recognize the user's emotions in real time. The data acquisition module collects physiological data through a built-in A / D (analog-to-digital) converter and transmits the physiological data to the emotion recognition module through the network for data analysis, processing and recognition.

[0036] The emotion recognition module includes a physiological data analysis unit, a physiological signal processing unit and a third-party emotion recognition algorithm unit. The physiological data analysis unit analyzes physiological data through text emotion, the physiological signal processing unit recognizes physiological signal processing data through voice emotion, and the third-party emotion recognition algorithm unit recognizes third-party emotion data through physiological emotion. The physiological data analysis unit, the physiological signal processing unit and the third-party emotion recognition algorithm unit are connected to the physiological data analysis module through a network.

[0037] The physiological data analysis module is used to parse the physiological data collected by the bracelet into digital signals that can be processed by the algorithm. The physiological data analysis module includes a physiological data calculation unit, a physiological signal calculation unit and a third-party emotion recognition algorithm unit. The physiological data calculation unit calculates the physiological abnormality score Fz based on the physiological data, the physiological signal calculation unit calculates the physiological stress comprehensive index Rz based on the physiological signal processing data, and the third-party emotion recognition algorithm unit calculates the upper emotion zone value Er and the lower emotion zone value Ei based on the third-party emotion data. The physiological data calculation unit, the physiological signal calculation unit and the third-party emotion recognition algorithm unit are connected to the intervention module through a network.

[0038] The data acquisition module mainly collects: physiological data including heart rate, blood oxygen, skin electrical response, user voice and environmental voice data.

[0039] The physiological data analysis unit numbers the heart rate variability data (HRV), the electrodermal activity data (EDA) and the heart rate data (HR) according to the physiological data characteristics. The heart rate variability data, the electrodermal activity data and the heart rate data are numbered X1, X2 and X3 respectively.

[0040] The physiological data calculation unit calculates the physiological abnormality score Fz according to the physiological data, and the calculation formula is:

[0041] Fz=a*X1+b*X2+c*X3

[0042] In the formula, Fz represents the physiological abnormality score, X1, X2, and X3 represent the heart rate variability data, the skin electrode activity data, and the heart rate data, respectively, and a, b, and c represent the weighted coefficients of the heart rate variability data, the skin electrode activity data, and the heart rate data in the physiological abnormality score, respectively.

[0043] The advantages are: by numbering and weighted calculation of the physiological abnormality score Fz, the smart bracelet device can monitor and evaluate the user's health status in real time and effectively, which helps the user to pay attention to his or her own physiological state in real time. At the same time, the smart bracelet can also provide an emergency warning when abnormalities appear in the heart rate variability data, skin electrode activity data and heart rate data, so as to make emergency treatment in advance to prevent health problems related to heart rate and skin. The promotion and application of the present invention is conducive to promoting the development of personal health management and enhancing people's awareness of and management capabilities of their own health.

[0044] The physiological signal processing unit numbers the resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain waves, blood pressure and blood sugar under the physiological stress state according to the physiological signal processing data characteristics. The resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain waves, blood pressure and blood sugar under the physiological stress state are numbered Y1, Y2, Y3, Y4, Y5, Y6, Y7 and Y8 respectively.

[0045] The physiological signal calculation unit calculates the physiological pressure comprehensive index Rz according to the physiological signal processing data, and the calculation formula is:

[0046]

[0047] In the formula, Rz represents the comprehensive index of physiological stress, Y1, Y2, Y3, Y4, Y5, Y6, Y7, and Y8 represent the resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain wave, blood pressure, and blood sugar under physiological stress, respectively. iIt represents an indicator under physiological stress state. e1, e2, e3, e4, e5, e6, e7, and e8 respectively represent the weighted coefficients of resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain wave, blood pressure, and blood sugar in the comprehensive physiological stress index under physiological stress state. i It represents the weighting coefficient of a certain indicator under physiological stress state.

[0048] The advantages are: by calculating the comprehensive physiological stress index Rz, when the comprehensive physiological stress index Rz exceeds 2 / 3 of the system's preset threshold, the intervention module can issue an early warning to remind the individual to take exercise relaxation measures to relieve stress, thereby providing auxiliary decision-making basis for medical professionals, helping the system to develop matching treatment plans for users, and by continuously monitoring and evaluating physiological stress status, it can help individuals better manage stress and promote physical and mental health.

[0049] The third-party emotion recognition algorithm unit numbers the intensity of emotion words, weight of degree adverbs and weight of negative words in the emotional fluctuation state of the smart bracelet according to the third-party emotion data characteristics. The intensity of emotion words in the emotional fluctuation state of the smart bracelet is numbered as T1, T2, T3, ...T n , the weights of degree adverbs in the emotional fluctuation state of the smart bracelet are numbered as v1, v2, v3, ...v n , the weights of negative words in the emotional fluctuation state of the smart bracelet are numbered as k1, k2, k3, ...k n .

[0050] The third-party emotion recognition algorithm unit calculates the upper emotion value Er based on the third-party emotion data, and the calculation formula is:

[0051]

[0052] In the formula, Er represents the upper emotional zone value, T1, T2, T3, ...T n Indicates the intensity of emotional words in the emotional fluctuation state of the smart bracelet, T i Indicates the intensity of a certain level of emotional words in the emotional fluctuation state of the smart bracelet, v1, v2, v3, ...v n Indicates the weight of degree adverbs in the emotional ups and downs of the smart bracelet, v i Indicates the weight of a degree adverb in the emotional ups and downs of the smart bracelet, k1, k2, k3, ...k n represents the weight of negative words in the emotional fluctuation state of the smart bracelet, k i Indicates the weight of a negative word in the emotional fluctuation state of the smart bracelet.

[0053] The third-party emotion recognition algorithm unit calculates the emotion lower zone value Ei according to the third-party emotion data, and the calculation formula is:

[0054]

[0055] In the formula, Ei represents the lower range of emotion, T1, T2, T3, ...T n Indicates the intensity of emotional words in the emotional fluctuation state of the smart bracelet, T i Indicates the intensity of a certain level of emotional words in the emotional fluctuation state of the smart bracelet, v1, v2, v3, ...v n Indicates the weight of degree adverbs in the emotional ups and downs of the smart bracelet, v i Indicates the weight of a degree adverb in the emotional ups and downs of the smart bracelet, k1, k2, k3, ...k n represents the weight of negative words in the emotional fluctuation state of the smart bracelet, k i Indicates the weight of a negative word in the emotional fluctuation state of the smart bracelet.

[0056] The advantages are: by calculating the upper emotion value Er and the lower emotion value Ei, the system can capture the dynamic range changes of emotions and reflect the real-time fluctuation degree of user emotions. Then, by quantifying emotions into specific numerical values, the emotional states of different time points or different users can be compared, thereby providing mental health monitoring for emotion recognition.

[0057] The intervention module is based on emotion recognition and combines the physiological abnormality score Fz, the comprehensive physiological stress index Rz, and the upper and lower emotional zone values ​​Er and Ei to generate personalized intervention suggestions. At the same time, the intervention module is used to recommend specific intervention suggestions and suggestion status to users.

[0058] The system of the present invention can detect user data in real time, analyze and infer the user's emotional state, establish a model based on intelligent algorithms, predict the user's psychological state, and can more comprehensively evaluate their mental health status. It can also provide personalized intervention suggestions, so that users can better manage their emotions and improve their mental health level.

[0059] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A mental state monitoring and evaluation system based on a smart bracelet, characterized in that: It includes interconnected smart bracelet body, cloud server and third-party mobile devices; The smart bracelet body includes a data acquisition module, an emotion recognition module, a physiological data analysis module and an intervention module; The data acquisition module collects the user's physiological data and uploads it to the cloud server for analysis and processing, and the emotion recognition module cooperates with the intervention module through the network. The emotion recognition module is used to recognize the user's emotions in real time. The data acquisition module collects physiological data through a built-in A / D converter and transmits the physiological data to the emotion recognition module through the network for data analysis, processing and recognition; The emotion recognition module includes a physiological data analysis unit, a physiological signal processing unit and a third-party emotion recognition algorithm unit. The physiological data analysis unit analyzes physiological data through text emotion, the physiological signal processing unit recognizes physiological signal processing data through voice emotion, and the third-party emotion recognition algorithm unit recognizes third-party emotion data through physiological emotion. The physiological data analysis unit, the physiological signal processing unit and the third-party emotion recognition algorithm unit are connected to the physiological data analysis module through a network; The physiological data analysis module is used to parse the physiological data collected by the bracelet into digital signals that can be processed by the algorithm. The physiological data analysis module includes a physiological data calculation unit, a physiological signal calculation unit and a third-party emotion recognition algorithm unit. The physiological data calculation unit calculates the physiological abnormality score Fz according to the physiological data, the physiological signal calculation unit calculates the physiological stress comprehensive index Rz according to the physiological signal processing data, and the third-party emotion recognition algorithm unit calculates the emotion upper zone value Er and the lower zone value Ei according to the third-party emotion data. The physiological data calculation unit, the physiological signal calculation unit and the third-party emotion recognition algorithm unit are connected to the intervention module through a network.

2. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 1 is characterized in that: The data acquisition module mainly collects: physiological data including heart rate, blood oxygen, skin electrical response, user voice and environmental voice data.

3. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 1 is characterized in that: The physiological data analysis unit performs data numbering on the heart rate variability data, the skin electrode activity data and the heart rate data according to the physiological data characteristics, and the heart rate variability data, the skin electrode activity data and the heart rate data are numbered X1, X2 and X3 respectively.

4. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 3 is characterized in that: The physiological data calculation unit calculates the physiological abnormality score Fz according to the physiological data, and the calculation formula is: Fz=a*X1+b*X2+c*X3 In the formula, Fz represents the physiological abnormality score, X1, X2, and X3 represent the heart rate variability data, the skin electrode activity data, and the heart rate data, respectively, and a, b, and c represent the weighted coefficients of the heart rate variability data, the skin electrode activity data, and the heart rate data in the physiological abnormality score, respectively.

5. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 1 is characterized in that: The physiological signal processing unit numbers the resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain waves, blood pressure and blood sugar under the physiological stress state according to the physiological signal processing data characteristics. The resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain waves, blood pressure and blood sugar under the physiological stress state are numbered Y1, Y2, Y3, Y4, Y5, Y6, Y7, Y8, respectively.

6. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 5 is characterized in that: The physiological signal calculation unit calculates the physiological pressure comprehensive index R according to the physiological signal processing data z , and its calculation formula is: In the formula, Rz represents the comprehensive index of physiological stress, Y1, Y2, Y3, Y4, Y5, Y6, Y7, and Y8 represent the resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain wave, blood pressure, and blood sugar under physiological stress, respectively. i It represents an indicator under physiological stress state. e1, e2, e3, e4, e5, e6, e7, and e8 respectively represent the weighted coefficients of resting heart rate, respiratory rate, blood oxygen saturation, skin temperature, muscle tension, brain wave, blood pressure, and blood sugar in the comprehensive physiological stress index under physiological stress state. i It represents the weighting coefficient of a certain indicator under physiological stress state.

7. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 1 is characterized in that: The third-party emotion recognition algorithm unit numbers the intensity of emotion words, weights of degree adverbs and weights of negative words in the emotional fluctuation state of the smart bracelet according to the third-party emotion data characteristics, and the intensity of emotion words in the emotional fluctuation state of the smart bracelet is numbered as T1, T2, T3, ... T n The weights of the degree adverbs in the emotional fluctuation state of the smart bracelet are numbered as v1, v2, v3, ...v n The weight numbers of negative words in the emotional fluctuation state of the smart bracelet are k1, k2, k3, ...k n .

8. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 7 is characterized in that: The third-party emotion recognition algorithm unit calculates the emotion upper zone value Er according to the third-party emotion data, and its calculation formula is: In the formula, Er represents the upper emotional zone value, T1, T2, T3, ...T n Indicates the intensity of emotional words in the emotional fluctuation state of the smart bracelet, T i Indicates the intensity of a certain level of emotional words in the emotional fluctuation state of the smart bracelet, v1, v2, v3, ...v n Indicates the weight of degree adverbs in the emotional ups and downs of the smart bracelet, v i Indicates the weight of a degree adverb in the emotional ups and downs of the smart bracelet, k1, k2, k3, ...k n represents the weight of negative words in the emotional fluctuation state of the smart bracelet, k i Indicates the weight of a negative word in the emotional fluctuation state of the smart bracelet.

9. The psychological state monitoring and evaluation system based on the smart bracelet according to claim 8 is characterized in that: The third-party emotion recognition algorithm unit calculates the emotion lower zone value Ei according to the third-party emotion data, and its calculation formula is: In the formula, Ei represents the lower range of emotion, T1, T2, T3, ...T n Indicates the intensity of emotional words in the emotional fluctuation state of the smart bracelet, T i Indicates the intensity of a certain level of emotional words in the emotional fluctuation state of the smart bracelet, v1, v2, v3, ...v n Indicates the weight of degree adverbs in the emotional ups and downs of the smart bracelet, v i Indicates the weight of a degree adverb in the emotional ups and downs of the smart bracelet, k1, k2, k3, ...k n represents the weight of negative words in the emotional fluctuation state of the smart bracelet, k i Indicates the weight of a negative word in the emotional fluctuation state of the smart bracelet.

10. The mental state monitoring and evaluation system based on the smart bracelet according to claim 9 is characterized in that: The intervention module generates personalized intervention suggestions based on emotion recognition and in combination with the physiological abnormality score Fz, the physiological stress comprehensive index Rz, and the emotional upper zone value Er and the lower zone value Ei. At the same time, the intervention module is used to recommend specific intervention suggestions and suggestion status to the user.

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