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CN-122025143-A - Closed-loop dynamic health management system and method based on intelligent ring

CN122025143ACN 122025143 ACN122025143 ACN 122025143ACN-122025143-A

Abstract

The invention relates to the technical field of life data health management and discloses a closed-loop dynamic health management system and method based on an intelligent ring; S11, acquiring continuous physiological data acquired by an intelligent ring with a physiological sensor, acquiring discontinuous subjective health data marked by a user through a matched application program, carrying out standardized cleaning on the acquired continuous physiological data and the discontinuous subjective health data, and encrypting and storing the data after cleaning to obtain continuous fusion data of the user. According to the invention, continuous physiological data acquired by the intelligent ring are accurately associated with subjective events and emotion data input by a user on a unified time axis, so that a data island is broken, and further, a dynamic weight adjustment is adopted to enable health scores to dynamically change according to personal shortboards and planned focuses, so that one-sidedness of a fixed weight algorithm is avoided.

Inventors

  • CHEN FANGHUA

Assignees

  • 宁波思屹创新科技有限公司

Dates

Publication Date
20260512
Application Date
20260204

Claims (10)

  1. 1. The closed-loop dynamic health management method based on the intelligent ring is characterized by being applied to electronic equipment and specifically comprising the following steps of: S11, acquiring continuous physiological data acquired by an intelligent ring with a physiological sensor of a user, acquiring discontinuous subjective health data marked by the user through a matched application program, carrying out standardized cleaning on the acquired continuous physiological data and the discontinuous subjective health data, and encrypting and storing the cleaned data to obtain continuous fusion data of the user; S12, acquiring continuous fusion data of a user to construct a weighted scoring system, wherein the weighted scoring system is used for calculating comprehensive health scores of the user, covers four dimensions of signs, diet, emotion management and daily events, maps the fusion data into basic scores of unified dimensions through a preset normalization function, and generates a multidimensional evaluation report reflecting the health state of the user and the comprehensive health scores; S13, acquiring individual characteristic images of a preset user, combining the individual characteristic images with the generated health evaluation results, generating a periodic personalized health plan, and converting conclusions in an evaluation report into executable tasks, wherein the executable tasks comprise sports, diet, sleep and pressure regulation blocks, each block is designed with a stepwise quantization target and an execution suggestion, and the stepwise targets gradually approach an ideal health target from the current capability level of the user in stages and are pushed to the user for execution in a fixed periodic form; S14, continuously collecting objective physiological response data of a user during the execution of the personalized health plan through an intelligent ring, and actively collecting subjective feedback of the user through an application program interface, wherein the subjective feedback comprises evaluation of plan execution difficulty, subjective feeling of physical conditions and adjustment suggestion of plan content, and simultaneously automatically recording plan execution behavior data of the user, including task punching completion rate, task execution duration and abandon rate; And S15, after the execution period of the personalized health plan is ended, comprehensively analyzing the collected objective physiological response data, subjective feedback data and plan execution behavior data, evaluating the actual effect of the health plan of the current period, dynamically adjusting a target set value, task content, execution frequency or difficulty step in the health plan of the next period based on the output evaluation result, and completing continuous self-adaptive evolution along with the change of the health state of the user.
  2. 2. The intelligent ring-based closed-loop dynamic health management method according to claim 1, wherein in S11, continuous physiological data collected by the intelligent ring with physiological sensor is obtained, and discontinuous subjective health data marked by the user is collected by the matched application program: The physiological data includes heart rate, heart rate variability, blood oxygen saturation and motion data; The subjective health data includes diet records, emotion tags, and daily event records.
  3. 3. The intelligent ring based closed loop dynamic health management method as set forth in claim 2, wherein said subjective health data comprises diet records, emotion tags and daily event records, comprising: The diet records comprise dining content, food material types, eating time and estimated components which are actively input or photographed and identified by a user, and the emotion tags are marked by selecting preset emotion states or inputting short descriptions in an application by the user, so that specific moments or events can be associated; The emotion labels and event records marked with time and physiological data in the same time period are subjected to association analysis, physiological response modes under specific emotion or activity are identified, subjective experience can be quantified through association, and the subjective experience is used as key input for evaluating the influence of life behaviors on physiological health, and accurate attribution and personalized guidance are realized in health evaluation and plan generation.
  4. 4. The closed-loop dynamic health management method based on an intelligent ring as set forth in claim 3, wherein the standardized cleaning of the collected continuous physiological data and discontinuous subjective health data, and the encrypted storage of the data after cleaning, comprises: Removing signal abnormal values caused by severe activities of users from continuous physiological data by adopting a motion artifact filtering algorithm, identifying and removing non-logical input from discontinuous subjective data through checking a data effective range, and complementing missing data points by adopting a time sequence-based interpolation algorithm to ensure continuity of the data on a time line; And (3) accurately matching and mapping the discrete subjective health events with continuous objective physiological signals in the window by setting a time window, so as to realize the association and fusion of the subjective and objective data in the space-time dimension, and then encrypting and storing the fused structured data set by using an AES encryption algorithm.
  5. 5. The intelligent ring based closed loop dynamic health management method as set forth in claim 4, wherein in S12, obtaining the continuous fusion data of the user to construct a weighted scoring system for calculating the comprehensive health score of the user, comprising: Constructing a core scoring system to cover physical sign, diet, emotion and event core dimensions based on the fusion data, wherein each dimension is further subdivided into a sub-dimension and a specific index, and the original data of each index is mapped into a unified basic score of 0-10 points through a preset linear or nonlinear normalization function; Introducing a dynamic weight mechanism to generate comprehensive scores, dynamically calculating the weights of the dynamic weight machine according to the continuous deviation of the personal baseline, the current plan key point and the data quality, and automatically improving the weights of the short-circuit indexes; For daily events, extracting structural feature vectors by NLP technology, inputting a pre-training machine learning model, combining physiological data fluctuation before and after the event, outputting quantitative impact scores of-10 to +10, finally integrating each basic score, event impact score and dynamic weight, and obtaining a comprehensive score reflecting the health condition of the user by weighting calculation.
  6. 6. The intelligent ring-based closed-loop dynamic health management method according to claim 5, wherein in S13, obtaining a preset individual feature image of the user and combining the generated health evaluation result to generate a periodic personalized health plan comprises: Invoking a pre-established user individual feature image, wherein the user individual feature image integrates static properties and dynamic behavior patterns of a user, and specifically comprises inherent information of age, gender and basic disease history, behavior pattern data of work and rest laws, exercise preferences and diet compliance, which are analyzed from historical data, and the inherent information, the behavior pattern data and a current health evaluation result are used as core input features; The core input feature inputs are converted to a specific executable periodic plan by a predefined rule base and a personalized plan is generated containing step-by-step up step goals and low salt diet recommendations in units of weeks.
  7. 7. The intelligent ring based closed loop dynamic health management method as in claim 6, wherein continuously collecting objective physiological response data of the user during execution of the personalized health plan through the intelligent ring while actively collecting subjective feedback of the user through the application interface in S14 comprises: During the execution of a health plan by a user, a physiological sensor arranged in an intelligent ring collects objective physiological response data in an adaptive mode, wherein the objective physiological response data comprises basic heart rate and blood oxygen saturation, indexes related to a plan target are monitored more intensively, and the actual influence of sleep structure change on a physiological state is analyzed finely during the sleep plan; and actively guiding user feedback at key nodes of plan execution through popping up questionnaires, sliding score bars or short dialogue interfaces, focusing collected contents on fatigue feeling after completing specific exercise tasks, satiety and actual effects of satisfaction feeling after adjusting diet and sleep-aiding suggestions, and subjective evaluation on overall difficulty and applicability of the plan.
  8. 8. The intelligent ring-based closed-loop dynamic health management method as set forth in claim 7, wherein in S15, after the personalized health plan execution cycle is ended, the collected objective physiological response data, subjective feedback data, and plan execution behavior data are comprehensively analyzed to evaluate the actual effect of the health plan of the current cycle, comprising: Performing multidimensional effect quantitative analysis after the planning period is finished, comparing the change trend and statistical significance of key health indexes before and after the period, calculating the achievement rate of a preset quantitative target of the exercise completion degree and the diet punching rate, and performing quantitative scoring TAR on collected subjective feedback evaluation of a user; Wherein, the calculation formula of the quantization score TAR is as follows: ; the actual completion amount Ak and the planning target amount Tk, wherein Ak can be the actual steps of the day, tk is the planning target steps, the ratio of the actual completion amount Ak and the planning target steps directly reflects the completion degree of a single item, and N is a numerical item of 1-k; the dynamic task weight Wk represents the importance of different tasks in the current period, the weight is dynamically distributed according to the health evaluation short plates and the planned core focus, and if the dietary fiber intake of the user does not reach the standard for a long time, the corresponding dietary card punching task weight is increased; to prevent excessive user movement or eating imbalance, however, an encouraging upper limit mu is set, and an additional but decreasing bonus score is given by a slowly increasing logarithmic function delta-ln, wherein the bonus coefficient delta both stimulates excessive completion and avoids unhealthy excessive pursuits; the quantization score TAR intuitively reflects the overall completion level of a user on a preset quantization target after the task weight and the reasonable excess are considered; Deep mining is carried out on the quantitative scores, plan concrete content, actual execution behavior data of users and final health improvement effect are taken as input, and intervention measures are recognized to be obviously related to forward health change through association rule learning.
  9. 9. A closed loop dynamic health management system based on an intelligent ring for performing the closed loop dynamic health management method of any of claims 1-8, said system comprising: the multi-source data fusion module is used for collecting and cooperatively processing continuous physiological data from the intelligent ring and subjective health data from the application program; the health dynamic evaluation module is used for constructing a multidimensional weighted scoring system based on the fusion data and calculating a comprehensive health score; The personalized plan generation module is used for generating a periodic and stepwise health plan by combining the individual feature portraits of the user with the health evaluation result; the execution feedback collection module is used for collecting objective physiological response data, subjective feedback and behavior compliance data during plan execution; And the iteration optimization module is used for analyzing the periodic execution effect, dynamically adjusting the health plan of the next period based on the evaluation result and realizing closed-loop self-adaptive management.
  10. 10. The intelligent ring-based closed-loop dynamic health management system of claim 9, wherein said health dynamic assessment module comprises: the dynamic weight calculation unit is used for dynamically adjusting the scoring weight according to the personal baseline deviation, the plan emphasis and the data credibility; And the event intelligent scoring unit is used for analyzing daily events through natural language processing and a machine learning model and outputting quantized health influence scores by combining the physiological data change trend.

Description

Closed-loop dynamic health management system and method based on intelligent ring Technical Field The invention relates to the technical field of life data health management, in particular to a closed-loop dynamic health management system and method based on an intelligent ring. Background Along with the rapid development of sensor technology, internet of things and mobile Internet, wearable equipment represented by intelligent watches and intelligent rings is widely popularized, a convenient hardware basis is provided for continuous acquisition of personal health data, the prior art scheme mainly focuses on two aspects, namely, on one hand, physical sign monitoring at a hardware end, such as continuous monitoring of heart rate and blood oxygen through photoplethysmography, the accelerometer is utilized to record movement steps and sleep states, the technical progress is mainly embodied in improvement of sensor precision and miniaturization of equipment, on the other hand, health data display and simple analysis at a software end are realized, most of matched application programs have a data billboard function, heart rate change, sleep structure, daily activity consumption and the like can be displayed in a chart form, and part of application also provides health suggestions based on general standards such as sleep score or fixed templates. However, the prior art scheme has significant defects on a critical path from data acquisition to effective health intervention, which results in limited health management effect, and difficulty in lasting user viscosity, and specifically comprises the following two points: 1. Physiological data collected by equipment, behavior data manually input by a user, subjective data such as emotion, life events and the like are usually stored in an isolated mode or simply listed, and the three-dimensional causal insight on the health state of the user cannot be formed due to lack of deep space-time correlation and fusion analysis; 2. Most scoring algorithms are single in dimension, and cannot take individual differences and dynamic fluctuation of health conditions into consideration, so that the evaluation result has limited reference value and the healthy short plates cannot be accurately positioned; Based on the foregoing, there is a need for a closed-loop dynamic health management method that can deeply fuse multidimensional data, provide individualization, and continuously self-optimize. Disclosure of Invention The invention aims to provide a closed-loop dynamic health management system and method based on an intelligent ring, which breaks through a data island by accurately correlating continuous physiological data acquired by the intelligent ring with subjective events and emotion data input by a user on a unified time axis, and further adopts dynamic weight adjustment to enable health scoring to dynamically change according to personal shortboards and planned focuses, so that one-sided performance of a fixed weight algorithm is avoided, and the problem in the prior art is solved. The invention discloses a closed-loop dynamic health management method based on an intelligent ring, which is applied to electronic equipment and specifically comprises the following steps of: S11, acquiring continuous physiological data acquired by an intelligent ring with a physiological sensor of a user, acquiring discontinuous subjective health data marked by the user through a matched application program, carrying out standardized cleaning on the acquired continuous physiological data and the discontinuous subjective health data, and encrypting and storing the cleaned data to obtain continuous fusion data of the user; S12, acquiring continuous fusion data of a user to construct a weighted scoring system, wherein the weighted scoring system is used for calculating comprehensive health scores of the user, covers four dimensions of signs, diet, emotion management and daily events, maps the fusion data into basic scores of unified dimensions through a preset normalization function, and generates a multidimensional evaluation report reflecting the health state of the user and the comprehensive health scores; S13, acquiring individual characteristic images of a preset user, combining the individual characteristic images with the generated health evaluation results, generating a periodic personalized health plan, and converting conclusions in an evaluation report into executable tasks, wherein the executable tasks comprise sports, diet, sleep and pressure regulation blocks, each block is designed with a stepwise quantization target and an execution suggestion, and the stepwise targets gradually approach an ideal health target from the current capability level of the user in stages and are pushed to the user for execution in a fixed periodic form; S14, continuously collecting objective physiological response data of a user during the execution of the personalized health plan through an intelligent ri