Physiological State Evaluation Using Context-Specific Correlation Functions
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Solution Overview
Problem
Current methods for evaluating a person's physiological state are limited in their ability to comprehensively and reliably determine nighttime and daytime stress and recovery, as well as the quality of sleep and exercise, often relying on single variables and lacking context information, which results in subjective and error-prone interpretations.
Innovation Solution
A method that measures and records physiological data over a continuous period, selecting multiple contexts such as night, day, sleep, and exercise, and uses preselected correlation functions to compute reference values for each context, combining them to determine the physiological state with improved reliability and objectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple contexts and variables are selected for comprehensive evaluation, then the reliability of physiological state determination is improved, but the device complexity and difficulty of operation increase
Solution Approach 1:
The evaluation system segments the physiological state determination into multiple distinct contexts (sleep, exercise, recovery, daily life) with specific variables for each context. This segmentation allows comprehensive evaluation while managing complexity by treating each context as a separate evaluable unit with its own criteria.
Solution Approach 2:
The system uses a universal evaluation framework that can handle multiple contexts and variables through a single integrated process. The same basic methodology (measuring physiological parameters, comparing against context-specific criteria, determining state) applies across all contexts, reducing operational complexity despite the comprehensive nature of the evaluation.
2Loss of information
If continuous measurement over extended periods is performed, then the completeness of context information is improved, but the loss of time and energy consumption increase
Solution Approach 1:
The system performs measurements in periodic cycles corresponding to different contexts (sleep periods, exercise sessions, daily life periods) rather than continuous monitoring. This allows comprehensive context information to be captured while reducing overall measurement time by focusing on relevant periodic intervals.
Solution Approach 2:
The system uses preselected criteria and reference values established before measurement to enable rapid evaluation during each context period. This preliminary preparation reduces the time needed for actual measurement and analysis during the extended evaluation period.
3Measurement precision
If interpretation depends on expert training and subjective judgment, then the measurement precision may be improved for complex cases, but the ease of operation and consistency decrease
Solution Approach 1:
The system performs automatic interpretation of physiological data by comparing measurements against preselected criteria and context-specific reference values. This self-service capability eliminates the need for expert subjective judgment while maintaining precision through objective, standardized evaluation rules that are consistently applied across all assessments.
Solution Approach 2:
The system transforms complex physiological data into simplified contextual parameters (sleep quality, exercise performance, recovery status) that can be automatically evaluated against predefined thresholds. This parameter transformation maintains measurement precision while greatly improving ease of operation by presenting results in an accessible format.
Data Source
AI summary
Disclosed is a method for evaluating a physiological state depicting a person's resources, in which method the alternatives of physiological states depicting resources are determined, one or more contexts are selected, one or more variables are selected for each context, in which case in the evaluation the person's physiological information is measured and recorded, the measurement-background data of the measurement are determined and recorded, a value is defined for a variable of the context, corresponding temporal periods are defined for each context, and the person's physiological state is determined. Further, in the method a preselected correlation function is defined, a value is computed for the correlation function, a reference value is computed for each physiological state, and the physiological state of the person is determined. A corresponding system employing the method for evaluating a person's physiological state is also disclosed.