Towards Improving Myocontrol of Prosthetic Hands: A Study on Automated Instability Detection
Meattini R, Nowak M, Melchiorri C, Castellini C (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: IEEE Computer Society
Book Volume: 2018-November
Pages Range: 374-380
Conference Proceedings Title: IEEE-RAS International Conference on Humanoid Robots
Event location: Beijing
ISBN: 9781538672839
DOI: 10.1109/HUMANOIDS.2018.8625021
Abstract
Myocontrol is the control of an assistive device via the interpretation of the subject's intent using surface electromyography, and one paradigmatic instance of myocontrol is in upper-limb prosthetics applications. The reliability of this kind of control remains a key issue - effective and stable upper-limb myocontrol is one of the most interesting open problems in the field of human-robot interfaces and rehabilitation. In this work we focused on the myocontrol of a prosthetic hand while grasping: performing grasp actions only when, and exactly for the duration, the user desires, avoiding failures that can lead to frustrating or catastrophic results. One specific step to improve stability in the myocontrol of prosthetic hands is the possibility to automatically detect the occurrence of a failure. For this purpose, the availability of an automatic 'oracle' able to accomplish this work enables the possibility of self-adaptation of the myocontrol system - e.g. via on-demand model updates for incremental learning. According to this view, we performed an experiment using a simplified but still realistic grasping protocol involving four able-bodied expert myocontrol users, and we extracted features from a state-of-the-art commercial prosthetic hand to automatically identify instability in the myocontrol. The results show that a standard classifier is able to detect failures with a mean balanced error rate of 15.98% over the subjects that took part in the experiments. Our results can also be potentially applied in non-medical applications such as, e.g., teleoperation using extra-light interfaces.
Authors with CRIS profile
Involved external institutions
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) / German Aerospace Center
Germany (DE)
University of Bologna / Università di Bologna
Italy (IT)
Germany (DE)
University of Bologna / Università di Bologna
Italy (IT)
How to cite
APA:
Meattini, R., Nowak, M., Melchiorri, C., & Castellini, C. (2018). Towards Improving Myocontrol of Prosthetic Hands: A Study on Automated Instability Detection. In IEEE-RAS International Conference on Humanoid Robots (pp. 374-380). Beijing, CN: IEEE Computer Society.
MLA:
Meattini, Roberto, et al. "Towards Improving Myocontrol of Prosthetic Hands: A Study on Automated Instability Detection." Proceedings of the 18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018, Beijing IEEE Computer Society, 2018. 374-380.
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