Adaptive Motor Rehabilitation Control With Real-Time Error Regulation
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Solution Overview
Problem
Existing robot-assisted motor rehabilitation systems face challenges in adapting error enhancement schemes to match the unique characteristics and needs of individual patients, leading to ineffective treatments for motor impairments.
Innovation Solution
A system that adaptively constructs an error regulation protocol tailored to each patient's specific characteristics, using sensors to measure movements and forces, and adjusts error enhancement and correction forces in real-time based on performance data to enhance motor therapy effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If error enhancement schemes are applied to robot-assisted rehabilitation systems, then patient motor performance improves, but the system cannot adapt to individual patient characteristics
Solution Approach 1:
The system dynamically adapts error enhancement parameters based on real-time measurement of patient performance. The control system continuously adjusts the magnitude and direction of error enhancement forces according to measured deviations from desired trajectories, enabling the system to adapt to each patient's unique characteristics while maintaining reliable motor performance improvement
Solution Approach 2:
The system employs feedback mechanisms where sensors measure patient movement parameters (position, velocity, acceleration) and the control system uses this measurement data to adjust error enhancement forces. This closed-loop feedback enables adaptation to individual patient characteristics by continuously monitoring performance and modifying treatment parameters accordingly
2Device complexity
If fixed error enhancement parameters are used, then system complexity is reduced, but treatment effectiveness for different patients decreases
Solution Approach 1:
The system performs self-adjustment by automatically measuring patient performance and computing optimal error enhancement parameters without requiring manual reconfiguration. The control system autonomously adapts treatment parameters based on real-time measurements, maintaining treatment effectiveness across different patients while avoiding the complexity of manual parameter setting
Data Source
AI summary
System and method for use in improving individual's motion ability are disclosed. A force applying device is used to apply a force to at least portion of the individual's body during an exercise performed by the individual. A sensing system monitors one or more training sessions of the exercise performed and selectively generate first measurement data comprising error-related data and second measurement data indicative of adaptive response of the individual to the force applied to the exercised body portion. A force controller can be used to manage operation of the force applying device according to operational data, such that the force being applied to the exercised body portion includes at least one of an interfering force segment or an assistive force segment, determined in accordance with a predetermined range of an error regulating profile.