Virtual Apparatus Modeling for Adaptive Rehabilitation Motion Control
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Solution Overview
Problem
Current rehabilitation systems face challenges in determining personalized treatment plans for patients, especially in remote medical assistance settings, where monitoring patient progress and adapting exercises based on personal characteristics is difficult for healthcare professionals located remotely from the patient.
Innovation Solution
A computer-implemented system that includes an electromechanical machine with motors and cables, controlled by a processing device, which generates motion profiles based on treatment plans and uses machine learning to assign patients to cohorts, dynamically control the exercise apparatus, and recommend or exclude treatment plans based on patient characteristics and desired outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If remote medical assistance is provided for rehabilitation, then patient accessibility to treatment is improved, but the ability to monitor patient progress and adapt exercises in real-time deteriorates
Solution Approach 1:
The system continuously collects patient performance data through sensors during exercise execution and feeds this information back to the healthcare professional via a network connection. The feedback includes real-time metrics such as range of motion, force applied, and exercise completion status, enabling the healthcare professional to monitor progress and adapt treatment plans remotely without losing critical patient information.
2Ease of manufacture
If standardized treatment plans are used, then implementation simplicity is improved, but personalization based on patient characteristics deteriorates
Solution Approach 1:
The treatment plan is not static but dynamically adjustable. The system allows healthcare professionals to modify exercise parameters, resistance levels, and treatment protocols based on real-time patient performance data and progress monitoring. This dynamic approach enables personalized treatment adaptation while maintaining the structured framework of standardized protocols, balancing simplicity with personalization.
3Adaptability or versatility
If comprehensive patient data collection is implemented, then treatment personalization is improved, but system complexity deteriorates
Solution Approach 1:
The data collection system is segmented into multiple independent components: sensors for physical measurements, user interface for patient information input, processing unit for data analysis, and communication module for data transmission. Each component handles specific data collection tasks independently, reducing overall system complexity while enabling comprehensive data gathering for personalized treatment.
4Productivity
If real-time exercise adjustment is enabled, then rehabilitation effectiveness is improved, but control system complexity deteriorates
Solution Approach 1:
The electromechanical exercise device incorporates automated control capabilities that adjust exercise parameters based on pre-programmed protocols and real-time sensor feedback. The system automatically modifies resistance, speed, and range of motion without requiring constant manual intervention, reducing control system complexity while maintaining real-time adjustment effectiveness for improved rehabilitation outcomes.
Data Source
AI summary
A computer-implemented system includes an electromechanical machine and a processing device communicatively coupled to motors. The processing device executes instructions to receive data comprising a treatment plan including one or more prescribed exercises for a user to perform using the electromechanical machine, generate, using a treatment machine description language and based on one or more desired goals of a user, a virtual apparatus model of the electromechanical machine, wherein the virtual apparatus model is generated by a trained machine learning model; and generate, using the virtual apparatus model and the data, a motion profile; and control, using the motion profile, the one or more motors.