Abstract
Access to early myoelectric training can be a crucial step in mastering prosthesis control. Controlling a prothesis is a cognitively demanding task with high rejection rates. Serious games not only provide patients with an opportunity to train their myoelectric control, but also help maintain their engagement throughout the extensive rehabilitation process. This work proposes a novel serious game design to train machine learning based myoelectric control, implemented in the form of a music-based app. The prototype of the game was evaluated by seven able-bodied participants and three clinical professionals with regard to system usability and motivation. Results showed positive outcomes in motivation, and a need for specific system usability improvements. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract

Abstract

Abstract
This work reports on preliminary findings about the learning process of a diverse set of users playing an immersive Virtual Reality serious game based on hand tracking to complement conventional occupational therapy in hand rehabilitation. Two test sessions with a one-day break between them were carried out with seven able-bodied participants. Participants went through twenty minutes guided functional task practice followed by a Semi-structured interview. The System Usability Scale (SUS) scores obtained for the first (75.36) and second (76.43) test sessions positioned the serious game above the average in terms of usability. Insights about the learning process., SUS and the obtained trial results., confirm the potential of the developed solution as a viable complement to conventional hand rehabilitation and highlight possible points for improvement. © 2021 IEEE.

Abstract