Activity-Rest Balance Scoring for Wearable Health Monitoring
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Solution Overview
Problem
Current wearable health monitoring devices fail to balance physical activity and rest, lacking the ability to correlate and manage these factors, which can lead to overtraining or undertraining, and do not provide users with automatic feedback or guidelines to achieve a healthier balance.
Innovation Solution
A method and system that collect and analyze sensor data to distinguish between sedentary stages and activity or rest, assigning intensity levels and evaluating activity-rest parameters to calculate an activity-rest score, providing feedback on the balance between physical activity and rest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If current wearable devices only measure physical activity without correlating rest, then device complexity is reduced and ease of operation is improved, but the ability to provide comprehensive health management and prevent overtraining deteriorates
Solution Approach 1:
The system integrates multiple functions into a single health monitoring platform: activity tracking, rest monitoring, balance calculation, and personalized guideline generation. The server performs comprehensive analysis of both activity and rest data to provide unified health management, making the device versatile while maintaining user-friendly operation through automated processing.
2Adaptability or versatility
If the system calculates activity-rest balance using multiple parameters and sensor data analysis, then health management capability is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent introduces a server as an intermediary component that handles complex computational tasks. The wearable device collects sensor data and transmits it to the server, which performs sophisticated analysis including distinguishing sedentary stages from activity/rest stages, evaluating multiple activity-rest parameters, and calculating the activity-rest balance. This mediator approach enables advanced health management while keeping the wearable device itself relatively simple.
3Productivity
If the system provides automated feedback and guidelines based on activity-rest balance, then user motivation and health outcomes are improved, but loss of information processing and computational overhead increase
Solution Approach 1:
The system implements a comprehensive feedback mechanism where the server continuously monitors activity and rest data, calculates the activity-rest balance using multiple parameters, and generates personalized guidelines. This feedback loop provides users with actionable insights about their training status (overtraining, undertraining, or balanced) and recommends specific adjustments to maintain optimal balance, thereby improving health outcomes through data-driven guidance.
Data Source
AI summary
Disclosed is a method for defining a balance between physical activity and rest for a user. The method comprises collecting sensor data indicative of a measure of activity performed and rest taken by the user as a function of time; analyzing the sensor data to distinguish sedentary stages from stages of activity or rest; assigning a level to a given stage of activity or rest; evaluating a plurality of activity-rest parameters for the user; and calculating an activity-rest score from the plurality of activity-rest parameters, so as to provide a feedback indicating a status of the balance between the physical activity and the rest.