Wireless Limb Sensor Association for Contralateral Movement Training
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Solution Overview
Problem
Current training systems do not effectively address contralateral movement exercises, which involve simultaneous movement of muscles on opposite sides of the body, failing to provide methods and systems that train individuals using such movements based on movement instructions.
Innovation Solution
An automated method for cognitive training using contralateral movement, employing motion tracking sensors attached to limbs of the human body to track and analyze limb movements in response to displayed instructions, determining correct matches and reaction times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion tracking sensors are used to track limb movements for cognitive training, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system automatically performs sensor-to-limb association by detecting which sensor corresponds to which body limb through motion patterns, eliminating the need for manual configuration. The sensors and processing system work together autonomously to identify and associate each sensor with its corresponding limb based on movement characteristics.
Solution Approach 2:
The system uses feedback from motion detection to automatically associate sensors with limbs. By monitoring movement patterns and comparing them against expected limb movement characteristics, the system refines its sensor-limb associations continuously, improving measurement precision while maintaining automated operation.
2Ease of operation
If automated sensor association is implemented, then ease of operation is improved, but reliability may worsen due to automatic detection errors
Solution Approach 1:
The system performs preliminary motion capture and analysis to establish sensor-limb associations before actual cognitive training begins. This preliminary action allows the system to pre-configure accurate associations based on initial movement patterns, ensuring reliability is established before operation starts.
Solution Approach 2:
The sensor-limb association is not static but dynamically adjustable. The system can re-evaluate and refine associations during operation based on continued motion feedback, allowing it to adapt to changes in sensor placement or user anatomy while maintaining ease of operation.
Data Source
AI summary
A method is provided for associating a plurality of wireless motion tracking sensors attached to limbs of a human body.