CN-122000063-A - Physical and mental health dynamic optimization system and method

CN122000063ACN 122000063 ACN122000063 ACN 122000063ACN-122000063-A

Abstract

The invention discloses a dynamic physical and mental health optimizing system and method, which belong to the technical field of physical and mental health management and comprise the following steps of S1, S2, S3, packaging into time sequence data streams, S4, constructing a contradiction theory model, and generating a physical and mental health situation report, evaluating physical and mental health and generating a personalized intervention scheme for dynamic intervention, wherein the physical and mental health is acquired, the physiological and mental and the behavioral three-dimensional data analysis is performed through time sequence data streams updated in a month and in real time, and the comprehensive evaluation effect and the timely intervention effect of the physical and mental health state can be improved in a multi-dimensional and real-time manner.

Inventors

ZHANG GUANGMING
WANG ZUSHU
LI HAIPENG

Assignees

天津慈壶科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260127

Claims (7)

1. The dynamic optimization method for physical and mental health is characterized by comprising the following steps of: S1, acquiring multi-mode data through active input of wearable equipment authorized by a user, a smart phone and the user, wherein the multi-mode data comprises physiological data, psychological data and behavioral data; S2, preprocessing the acquired multi-modal data to construct a multi-modal health baseline including a physiological health baseline, a psychological health baseline and a behavioral health baseline; s3, packaging the preprocessed multi-mode data into a time sequence data stream according to the same time stamp, wherein the time sequence data stream comprises time stamps, physiological data, psychological data and behavior data; S4, constructing a contradiction theory model, wherein the three-dimensional contradiction field boundary is respectively a physiological dimension, a psychological dimension and a behavioral dimension, the contradiction elements are respectively abnormal states of each dimension, the contradiction intensity quantification rule is a contradiction element abnormality degree, a contradiction element association degree and a contradiction element weight product, a contradiction judgment threshold value is preset, the contradiction element abnormality degree and the contradiction element association degree are calculated based on a time sequence data stream, the contradiction intensity quantification rule is substituted into the contradiction intensity quantification rule to calculate the intensity of each contradiction element, and the main contradiction and the secondary contradiction affecting the physical and mental health state are distinguished by comparing with the contradiction judgment threshold value; S5, generating a physical and mental health situation report based on the main contradiction and the secondary contradiction, evaluating physical and mental health, generating a personalized intervention scheme and performing dynamic intervention.
2. The method for dynamically optimizing physical and mental health according to claim 1, wherein in step S2, the step of constructing the multi-modal health baseline comprises the steps of: a multi-modal health baseline was generated based on the mean 2-fold standard deviation of the normalized multi-modal data for the last month.
3. The method for dynamically optimizing physical and mental health according to claim 2, wherein in step S4, the step of calculating the degree of abnormality of the contradictory elements based on the time series data stream comprises: Dividing physiological data, psychological data and behavioral data in a time sequence data stream updated in real time for nearly one month into continuous segments through a sliding window; Extracting time sequence characteristics of each segment, including time domain characteristics, frequency domain characteristics and nonlinear characteristics; the time sequence characteristics of the fragments and the time sequence characteristics of the healthy base lines are matched through a dynamic time warping algorithm, and when the dynamic time warping distance is larger than a preset threshold value, the time sequence is judged to be abnormal, and the time sequence is marked as contradictory elements of corresponding dimensions; a time sequence abnormality list is generated by the data determined to be time sequence abnormality, the time sequence abnormality list comprises contradiction elements, abnormality starting and ending time and abnormality degree, and the abnormality degree is taken as the abnormality degree of the contradiction elements.
4. The method for dynamically optimizing physical and mental health as recited in claim 3, wherein in step S4, the step of calculating the association degree of contradictory elements based on the time series data stream comprises the steps of: integrating the abnormal data of the same user and the time stamp in the time sequence abnormal list into a transaction data set; mining frequently occurring contradictory combinations in the transaction data set through an Apriori algorithm; and generating a correlation rule list based on the mined frequently-occurring contradiction combinations, wherein the association rule list comprises precondition contradiction, conclusion contradiction, confidence and support degree, and the confidence is used as the association degree of contradiction elements.
5. The method for dynamically optimizing physical and mental health according to claim 4, wherein in step S5, the step of generating the physical and mental health status report comprises the steps of: Presetting a mapping rule of abnormality degree and physical and mental health risk level of contradiction elements; judging the physical and mental health risk level trend based on the abnormality degree trend of the main contradiction and the secondary contradiction; generating a physical and mental health situation report based on the physical and mental health risk grade trend; And evaluating the physical and mental health state based on the physical and mental health situation report.
6. The method for dynamically optimizing physical and mental health according to claim 5, wherein in step S5, the step of dynamically intervening comprises the steps of: Collecting physical and mental health intervention strategy data and constructing an intervention strategy database; presetting a mapping rule of a physical and mental health situation report and an intervention strategy database; and generating a personalized intervention scheme based on the generated physical and mental health situation report.
7. The dynamic physical and mental health optimizing system according to claim 6, comprising: The multi-mode data acquisition module (1) acquires multi-mode data through active input of wearable equipment authorized by a user, a smart phone and the user, wherein the multi-mode data comprises physiological data, psychological data and behavioral data; The health baseline construction module (2) is used for preprocessing the acquired multi-modal data to construct a multi-modal health baseline, wherein the multi-modal health baseline comprises a physiological health baseline, a psychological health baseline and a behavioral health baseline; The multi-mode data fusion module (3) packages the preprocessed multi-mode data into a time sequence data stream according to the same time stamp, wherein the time sequence data stream comprises the time stamp, physiological data, psychological data and behavior data; The contradiction analysis module (4) constructs a contradiction theory model, wherein the three-dimensional contradiction field boundary is respectively a physiological dimension, a psychological dimension and a behavioral dimension, the contradiction elements are respectively abnormal states of each dimension, the contradiction intensity quantification rule is a contradiction element abnormality degree, a contradiction element association degree and a contradiction element weight product, a contradiction judgment threshold value is preset, the contradiction element abnormality degree and the contradiction element association degree are calculated based on a time sequence data stream, the contradiction intensity quantification rule is substituted into the contradiction intensity quantification rule to calculate the intensity of each contradiction element, and the main contradiction and the secondary contradiction affecting the physical and mental health state are distinguished by comparing with the contradiction judgment threshold value; The health situation assessment module (5) is used for generating a physical and mental health situation report based on the main contradiction and the secondary contradiction and assessing physical and mental health; and the dynamic intervention module (6) is used for generating a personalized intervention scheme based on the physical and mental health situation report and performing personalized intervention.

Description

Physical and mental health dynamic optimization system and method Technical Field The invention belongs to the technical field of physical and mental health management, and particularly relates to a physical and mental health dynamic optimization system and method. Background Physical and mental health management is a dynamic process for comprehensively monitoring, evaluating, regulating and optimizing physiological functions, psychological states, behavioral habits and social adaptability by taking the collaborative development of physiological health and psychological health of individuals or groups as a core target and establishing a systematic and personalized intervention and maintenance system through integrating multidisciplinary theories and methods such as medicine, psychology, sports science, nutrition, behavior management and the like. The current physical and mental health management generally focuses on single-dimension or hysteresis intervention, for example, health monitoring is often limited to the tracking of physiological indexes, psychological health is often dependent on subjective scales or periodical psychological consultation, real-time and seamless integration and early intervention are difficult to realize, while AI application can perform simple dialogue or provide standardized content, dynamic understanding of a complex social and psychological field where an individual is located is lacking, core contradiction affecting health cannot be fundamentally identified and reconciled, so that the intervention effect is limited and the persistence is insufficient, in addition, data islanding phenomenon is common, physiological, psychological and environmental data are mutually split, and comprehensive insight on the health state of the individual is difficult to form. In view of this, a system and a method for dynamic optimization of physical and mental health are designed to solve the above problems. Disclosure of Invention To solve the problems set forth in the background art. The invention provides a dynamic optimization system and method for physical and mental health, which have the characteristics of being multidimensional and capable of improving the overall evaluation effect and the timely intervention effect of the physical and mental health state in real time. In order to achieve the purpose, the invention provides the following technical scheme that the physical and mental health dynamic optimization method comprises the following steps: S1, acquiring multi-mode data through active input of wearable equipment authorized by a user, a smart phone and the user, wherein the multi-mode data comprises physiological data, psychological data and behavioral data; S2, preprocessing the acquired multi-modal data to construct a multi-modal health baseline including a physiological health baseline, a psychological health baseline and a behavioral health baseline; s3, packaging the preprocessed multi-mode data into a time sequence data stream according to the same time stamp, wherein the time sequence data stream comprises time stamps, physiological data, psychological data and behavior data; S4, constructing a contradiction theory model, wherein the three-dimensional contradiction field boundary is respectively a physiological dimension, a psychological dimension and a behavioral dimension, the contradiction elements are respectively abnormal states of each dimension, the contradiction intensity quantification rule is a contradiction element abnormality degree, a contradiction element association degree and a contradiction element weight product, a contradiction judgment threshold value is preset, the contradiction element abnormality degree and the contradiction element association degree are calculated based on a time sequence data stream, the contradiction intensity quantification rule is substituted into the contradiction intensity quantification rule to calculate the intensity of each contradiction element, and the main contradiction and the secondary contradiction affecting the physical and mental health state are distinguished by comparing with the contradiction judgment threshold value; S5, generating a physical and mental health situation report based on the main contradiction and the secondary contradiction, evaluating physical and mental health, generating a personalized intervention scheme and performing dynamic intervention. Further, in step S2, the step of constructing the multi-modal health baseline includes: a multi-modal health baseline was generated based on the mean 2-fold standard deviation of the normalized multi-modal data for the last month. Further, in step S4, the step of calculating the degree of abnormality of the contradictory elements based on the time-series data stream includes: Dividing physiological data, psychological data and behavioral data in a time sequence data stream updated in real time for nearly one month into continuous segments through a sliding