User-informed Design and Early Evaluation of a Mobile Virtual Reality System for Training and Assessment of Myoelectric Prosthesis Control

Abstract

Myoelectric control uses surface EMG signals from muscle contractions to operate prosthetic limbs. However, learning intuitive myoelectric control of multi-joint movements and diverse grasp patterns remains a major challenge for broader user adoption of multi-articulating prosthetic hands. The training required to attain these control skills is intensive and often inaccessible in areas with limited rehabilitation resources. To address this gap, we developed a mobile virtual reality (VR) solution that offers multi-articulating prosthetic training and assessment in ecologically valid tasks. We evaluate platform usability through real-time performance metrics capturing user interactions, and semi-structured interviews capturing end-user perspectives, conducted during VR training sessions with a clinician and a participant with upper-limb loss (ULL). Training and assessment functionalities were examined, and users reported positive usability outcomes. These findings suggest our VR platform’s potential as an accessible and effective prosthetic rehabilitation tool in remote areas.