Virtual Physiotherapy Trainer With 3D Pose Feedback
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Solution Overview
Problem
Conventional physical therapy programs lack an enjoyable user experience, fail to promote patient compliance, and do not provide effective feedback on exercise performance, leading to increased healthcare costs and limited positive outcomes.
Innovation Solution
A computer-implemented system using a 3D camera and low-cost CPU/GPU architecture for real-time motion capture and analysis, generating an interactive avatar that provides corrective feedback and encouragement, capable of operating under challenging environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional physical therapy programs are used, then healthcare costs increase and patient outcomes are limited, but they fail to provide enjoyable user experience, patient compliance promotion, and useful feedback on exercise performance
Solution Approach 1:
The patent creates a virtual copy of a physical therapist through an AI-driven avatar that replicates therapist functions including exercise demonstration, real-time performance monitoring, and feedback provision. This virtual copy enables patients to receive consistent, high-quality guidance at home without requiring continuous in-person therapist involvement, thereby improving outcomes while reducing costs.
Solution Approach 2:
The system implements real-time feedback mechanisms where the AI avatar continuously monitors patient exercise performance through computer vision, compares it against correct form, and provides immediate corrective feedback. This continuous feedback loop ensures patients perform exercises correctly, maximizing therapeutic benefit and compliance.
2Measurement precision
If real-time motion capture and analysis is implemented, then accurate feedback and guidance are provided, but system complexity and computational requirements increase
Solution Approach 1:
The patent replaces complex mechanical motion capture systems with computer vision-based tracking using standard cameras. The AI avatar analyzes patient movement through 2D/3D pose estimation from video feeds, eliminating the need for expensive motion capture equipment while maintaining measurement precision through advanced image processing algorithms.
Solution Approach 2:
The system performs self-calibration and automatic setup by detecting the patient's position and environment, adjusting parameters automatically without requiring manual configuration. The AI avatar independently monitors and corrects exercise form, providing autonomous operation that reduces system complexity.
3Adaptability or versatility
If the system operates under challenging environmental conditions, then home-based use is enabled, but measurement accuracy and reliability may deteriorate
Solution Approach 1:
The system dynamically adapts to varying environmental conditions by adjusting camera parameters, lighting compensation, and pose estimation thresholds in real-time. The AI avatar continuously calibrates to the patient's starting position and environmental factors, maintaining measurement accuracy across different home settings regardless of lighting, space, or background variations.
Data Source
AI summary
A telehealth training system is provided which employs a three-dimensional camera programmed for capturing image data associated with an exercise program performed by a user. A computer-implemented body pose analysis and scoring module analyzes and scores body poses of the user while the user performs the exercise program. The analysis and scoring module may calculate scores in response to reference data related to at least one exercise prescribed for the user, and then compare processing results to the reference data. A feedback module may be included in the system which is programmed for creating and animating an avatar in response to the processing results of the analysis and scoring module. In certain aspects, the analysis and scoring module may be programmed for using a voxel basis function (VBF) technique in connection with performing pose matching analysis in association with the user performing the exercise program.