Using Capability Maps Tailored to Arm Range of Motion in VR Exergames for Rehabilitation

TL;DR

This paper introduces a method using capability maps based on arm range of motion to personalize VR-based rehabilitation for neurological patients, enhancing engagement and progress tracking.

Contribution

It presents a novel approach to tailor VR rehabilitation programs by integrating arm kinematic modeling and capability maps, enabling personalized therapy.

Findings

Capability maps effectively represent user arm motion limitations.

The system can adapt VR exercises based on individual capabilities.

Assessment of specific upper limb joints is feasible within this framework.

Abstract

Many neurological conditions, e.g., a stroke, can cause patients to experience upper limb (UL) motor impairments that hinder their daily activities. For such patients, while rehabilitation therapy is key for regaining autonomy and restoring mobility, its long-term nature entails ongoing time commitment and it is often not sufficiently engaging. Virtual reality (VR) can transform rehabilitation therapy into engaging game-like tasks that can be tailored to patient-specific activities, set goals, and provide rehabilitation assessment. Yet, most VR systems lack built-in methods to track progress over time and alter rehabilitation programs accordingly. We propose using arm kinematic modeling and capability maps to allow a VR system to understand a user's physical capability and limitation. Next, we suggest two use cases for the VR system to utilize the user's capability map for tailoring rehabilitation programs. Finally, for one use case, it is shown that the VR system can emphasize and assess the use of specific UL joints.