Augmented Reality Limb Rendering for Range-of-Motion Therapy
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Solution Overview
Problem
There is a lack of virtual-reality body-tracking therapy systems that provide automated therapy sessions effectively, despite the existence of virtual reality body-tracking systems for gaming and sports training, as existing systems do not adequately address the need for therapy-specific interventions.
Innovation Solution
An augmented-reality range-of-motion therapy system that uses processor-based methods to obtain activity and anatomical information, determine expected range-of-motion, track user body parts, and render augmented-reality limbs for therapy, providing feedback on discrepancies in range-of-motion compared to a threshold value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If virtual reality body-tracking systems are used for gaming and sports training, then user engagement and entertainment value are improved, but therapeutic effectiveness and medical accuracy deteriorate
Solution Approach 1:
The system segments the application domain by creating separate tracking models for therapeutic exercises versus gaming/sports activities. The processor identifies the specific therapy being performed and applies specialized tracking parameters and range-of-motion thresholds appropriate for medical rehabilitation, while maintaining engagement through AR visual feedback.
Solution Approach 2:
The system implements real-time feedback mechanisms that provide therapeutic guidance through augmented reality visual cues. The AR device displays visual indicators showing correct movement paths, range-of-motion boundaries, and performance feedback, enabling users to self-correct while maintaining engagement without compromising therapeutic accuracy.
2Productivity
If automated therapy sessions are implemented, then therapist time and resources are reduced, but measurement precision and monitoring accuracy worsen
Solution Approach 1:
The system replaces manual therapist measurement and monitoring with an automated optical tracking system. The processor continuously captures body position data from video feeds, calculates range-of-motion parameters algorithmically, and compares measurements against predefined therapeutic thresholds, maintaining precision while enabling automated high-volume therapy delivery.
Solution Approach 2:
The system introduces an intermediary computational layer that acts between the user's physical movements and the therapeutic assessment. The processor serves as a mediator that translates raw video data into meaningful range-of-motion measurements, applies medical expertise through programmed protocols, and provides feedback without requiring direct therapist intervention for each measurement.
3Ease of manufacture
If body tracking applications are adapted from gaming to therapy, then development cost and time are reduced, but adaptability to specific therapeutic needs deteriorates
Solution Approach 1:
The system implements dynamic adaptability where the tracking parameters, range-of-motion thresholds, and feedback mechanisms are not fixed but can be adjusted based on the specific therapy being delivered. The processor dynamically modifies tracking sensitivity and acceptance criteria according to the therapeutic protocol, allowing the same hardware platform to adapt to diverse rehabilitation needs.
Solution Approach 2:
The system creates a universal platform that can deliver multiple different therapeutic exercises and protocols through a single integrated system. By implementing a configurable framework with programmable therapy protocols and adjustable parameters, the system maintains the efficiency of a unified platform while adapting to specific therapeutic requirements through software configuration rather than hardware changes.
Data Source
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AI summary
A server to perform a selected therapy on a user. The system may include a processor which may obtain activity information (AI) including information related to one or more of augmented-reality (AR) activity information, AR anatomical feature information, and range-of-motion (ROM) information; obtain user information including information related to one or more of the anatomy and physiology of the user; determine expected range-of-motion (EROM) information in accordance with the AI and the user information; track selected body parts (SBPs) of the user corresponding with the AR anatomical feature information; and/or render one or more augmented-reality limbs (ARLs) in relation with one or more corresponding SBPs of the user on a display of the system.