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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Neurorobot. | doi: 10.3389/fnbot.2019.00068

Automated Instability Detection for Interactive Myocontrol of Prosthetic Hands

  • 1University of Bologna, Italy
  • 2Institute of Robotics and Mechatronics, German Aerospace Center, Helmholtz Association of German Research Centers (HZ), Germany

Myocontrol is control of a prosthetic device by a disabled user using data obtained non- or minimally-invasively from (residual) muscle activity. In most myocontrol prosthetic systems, such biological data also denote the subject’s intent: reliably interpreting what the user wants to do, exactly and only when she wants, is paramount to avoid instability, potentially leading to accidents, humiliation and trauma. Indeed, instability manifests itself as a failure of the myocontrol in interpreting the subject’s intent, and the automated detection of such failures can be a specific step to improve myocontrol of prostheses — e.g. enabling the possibility of self-adaptation of the system via on-demand model updates for incremental learning, i.e. the interactive myocontrol paradigm.
In this work we engaged six expert myocontrol users (five able-bodied subjects and one trans-radial amputee) in a simple, clear grasp-carry-release task, in which the subject’s intent was reasonably determined by the task itself. We then manually ascertained when the intent would not coincide with the behaviour of the prosthetic device, i.e., we labelled the failures of the myocontrol system. Lastly, we trained and tested a classifier to automatically detect such failures. Our results show that a standard classifier is able to detect myocontrol failures with a mean balanced error
rate of 18.86% over all subjects.
If confirmed in the large, this approach could pave the way to self-detection and correction of myocontrol errors, a tighter man-machine co-adaptation, and in the end the improvement of the reliability of myocontrol.

Keywords: Myocontrol, instability, Reliability, Interactive Myocontrol, prosthesis control, amputee

Received: 20 Jan 2019; Accepted: 12 Aug 2019.

Edited by:

Ricardo Chavarriaga, École Polytechnique Fédérale de Lausanne, Switzerland

Reviewed by:

Noman Naseer, Air University, Pakistan
Aymar De Rugy, Centre National de la Recherche Scientifique (CNRS), France  

Copyright: © 2019 Meattini, Nowak, Melchiorri and Castellini. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: PhD. Roberto Meattini, University of Bologna, Bologna, Italy, roberto.meattini2@unibo.it