Readiness Score Calculation Using Wearable Biosignal Segmentation
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Solution Overview
Problem
Conventional devices that monitor physical and biological signals of individuals do not assess readiness scores or provide information on recovery from mental and physical loads, nor do they analyze health parameters in detail, failing to offer personalized recommendations for improving readiness.
Innovation Solution
A method and system that measure user movements and biosignals during activity and rest periods, calculate a readiness score based on body response summaries, and provide personalized instructions for improving readiness through a wearable ring, mobile device, and server communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional devices monitor physical and biological signals, then basic health data collection is achieved, but readiness score assessment and recovery information are not provided
Solution Approach 1:
The system segments the readiness assessment into multiple components: activity period analysis, rest period analysis, body response evaluation, and readiness score calculation. Each component processes specific data types (movements, biosignals) and produces intermediate results that are combined to form the comprehensive readiness assessment, preventing information loss while managing complexity through modular processing
Solution Approach 2:
The wearable device serves multiple functions: it monitors physical activity, tracks biological signals, determines period nature (activity/rest), calculates readiness scores, and provides recovery recommendations. This multi-functional approach consolidates what would otherwise require multiple separate devices into a single universal platform, addressing information loss without proportionally increasing system complexity
2Measurement precision
If detailed analysis of health parameters is performed, then readiness score accuracy is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary organization of data during collection, categorizing movements and biosignals by period type (activity/rest) as data arrives. This pre-structuring of data during the monitoring phase reduces the computational burden during analysis, enabling detailed processing without excessive time delays when readiness scores need to be calculated
Solution Approach 2:
The system continuously processes data streams in real-time, maintaining a rolling analysis of activity and rest periods. Rather than batch-processing all historical data, the system continuously updates readiness assessments by incorporating new data while maintaining context from previous periods, ensuring both accuracy and timely delivery of results
3Adaptability or versatility
If personalized recommendations are provided, then user recovery management is improved, but system complexity increases
Solution Approach 1:
The system implements feedback loops where readiness scores and recovery recommendations are provided to users based on their monitored data. User responses to recommendations and changes in readiness over time feed back into the system, allowing it to adapt and personalize future recommendations. This feedback mechanism enables personalization without requiring complex manual configuration
Solution Approach 2:
The system automatically generates personalized recovery recommendations by analyzing the user's own data patterns without requiring external intervention. It self-adjusts to individual user behaviors, activity patterns, and physiological responses, providing tailored guidance autonomously. This self-service capability delivers personalization while keeping the system architecture relatively simple
Data Source
AI summary
A method and a system for assessing readiness of a user, the method including obtaining the user's movements; using the obtained user's movements to determine a nature of the period, wherein the nature of the period is selected from an activity period and a rest period; measuring at least one biosignal of the user during the rest period; determining a rest summary for the rest period, based on the measured at least one biosignal and at least one biosignal of a previous rest period; determining an activity summary for the activity period, based on the obtained movements of an activity period and obtained movements of at least one previous activity period; determining a body response summary based on the rest summary and the activity summary; and calculating a readiness score based on the body response summary and a previous body response summary, whereby the readiness score indicates a level of readiness of the user.