Wearable Device Physical Stability Prediction
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Solution Overview
Problem
Current methods for determining physical stability of workers in hazardous environments rely on subjective judgments, leading to inaccuracies and increased risks of loss of life and property damage due to decreased concentration.
Innovation Solution
A system and method using a wearable device to collect sleep, activity, and heartbeat information, processing this data through semi-supervised learning to calculate a physical stability rating, which includes determining sleep state, activity intensity, and heartbeat state, and adjusting job difficulty accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If subjective judgment by manager or co-worker is used to determine physical stability, then the determination process is simple, but the accuracy of determination decreases
Solution Approach 1:
The patent replaces the mechanical/manual system of subjective visual judgment with an automated electronic system that collects physiological data (heart rate, activity levels, sleep patterns) through wearable devices and processes it through algorithms to objectively determine physical stability, thereby improving accuracy while maintaining operational simplicity
Solution Approach 2:
The patent introduces wearable devices and data processing systems as intermediaries between the worker's physiological state and the stability determination, allowing accurate measurement of physical stability without requiring direct subjective assessment by managers or co-workers
2Reliability
If multiple physiological parameters are collected and processed through semi-supervised learning, then the reliability of physical stability rating increases, but the device complexity increases
Solution Approach 1:
The patent employs a multi-functional wearable device that simultaneously collects multiple physiological parameters (heart rate, activity, sleep data) through integrated sensors, and processes this data through semi-supervised learning algorithms to generate comprehensive physical stability ratings, achieving high reliability through a single unified system rather than multiple separate systems
Solution Approach 2:
The patent performs preliminary data collection and processing by continuously monitoring physiological parameters and pre-processing the data through semi-supervised learning algorithms before final stability determination, allowing the system to maintain high reliability while managing complexity through advance preparation and automated processing
Data Source
AI summary
A physical stability determination system includes a wearable device configured to collect sleep information, activity information and heartbeat information of a user, a data preprocessor configured to divide each of the activity information and the heartbeat information into data of a sleep area and data of an activity area, based on the sleep information, and a data processor configured to calculate a sleep state, an activity intensity or a heartbeat state of the user from the data of the sleep area and the data of the activity area. The data of the sleep area may be used to calculate the sleep state in the data processor, and the data of the activity area may be used to calculate the activity intensity or the heartbeat state in the data processor.