A Recipe for Unsupervised Myocontrol - Co-Adaptive Training and Assessment in Physics-Based VR

Robra L, Egle F, Braun H, Pasquali A, Bargellini D, Meattini R, Castellini C (2026)

Publication Type: Journal article

Publication year: 2026

Journal

IEEE Transactions on Medical Robotics and Bionics IEEE

Original Authors: Lisa Robra, Fabio Egle, Hannah Braun, Alex Pasquali, Davide Bargellini, Roberto Meattini, Claudio Castellini

DOI: 10.1109/TMRB.2026.3746707

Abstract

Myoelectric prostheses can enable intuitive control, yet achieving natural and reliable movements remains challenging and contributes to device abandonment. We present a physics-based virtual reality (VR) environment for co-adaptive training of an unsupervised incremental non-negative matrix factorization (iNMF) control scheme for hand prostheses. The VR system includes three scenarios covering initialization, closed-loop user–controller co-adaptation, and evaluation during activities of daily living (ADL). Feasibility was examined in a pilot study with five participants using task performance, reconstruction error, and perceived workload (NASA-TLX). During co-adaptation, reconstruction error generally decreased with participant-specific variability, and post-training models better reconstructed ADL data than the initialization model. VR task performance improved across repetitions, indicating learning and adaptation, while workload tended to decrease with longer training but increased for more complex ADL tasks. Overall, the results support the feasibility of VR-based training for unsupervised prosthetic myocontrol.

Authors with CRIS profile

Lisa Robra Assistive Intelligent Robotics Lab Fabio Egle Assistive Intelligent Robotics Lab Hannah Braun Assistive Intelligent Robotics Lab Claudio Castellini Assistive Intelligent Robotics Lab

Involved external institutions

University of Bologna / Università di Bologna IT Italy (IT)

How to cite

APA:

Robra, L., Egle, F., Braun, H., Pasquali, A., Bargellini, D., Meattini, R., & Castellini, C. (2026). A Recipe for Unsupervised Myocontrol - Co-Adaptive Training and Assessment in Physics-Based VR. IEEE Transactions on Medical Robotics and Bionics. https://doi.org/10.1109/TMRB.2026.3746707

MLA:

Robra, Lisa, et al. "A Recipe for Unsupervised Myocontrol - Co-Adaptive Training and Assessment in Physics-Based VR." IEEE Transactions on Medical Robotics and Bionics (2026).

BibTeX: Download