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A novel percutaneous electrode implant for improving robustness in advanced myoelectric control

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Title: A novel percutaneous electrode implant for improving robustness in advanced myoelectric control
Authors: Hahne, JM
Farina, D
Jiang, N
Liebetanz, D
Item Type: Journal Article
Abstract: Despite several decades of research, electrically powered hand and arm prostheses are still controlled with very simple algorithms that process the surface electromyogram (EMG) of remnant muscles to achieve control of one prosthetic function at a time. More advanced machine learning methods have shown promising results under laboratory conditions. However, limited robustness has largely prevented the transfer of these laboratory advances to clinical applications. In this paper, we introduce a novel percutaneous EMG electrode to be implanted chronically with the aim of improving the reliability of EMG detection in myoelectric control. The proposed electrode requires a minimally invasive procedure for its implantation, similar to a cosmetic micro-dermal implant. Moreover, being percutaneous, it does not require power and data telemetry modules. Four of these electrodes were chronically implanted in the forearm of an able-bodied human volunteer for testing their characteristics. The implants showed significantly lower impedance and greater robustness against mechanical interference than traditional surface EMG electrodes used for myoelectric control. Moreover, the EMG signals detected by the proposed systems allowed more stable control performance across sessions in different days than that achieved with classic EMG electrodes. In conclusion, the proposed implants may be a promising interface for clinically available prostheses.
Issue Date: 31-Mar-2016
Date of Acceptance: 7-Mar-2016
URI: http://hdl.handle.net/10044/1/44388
DOI: https://dx.doi.org/10.3389/fnins.2016.00114
ISSN: 1662-4548
Publisher: Frontiers Media
Journal / Book Title: Frontiers in Neuroscience
Volume: 10
Copyright Statement: © 2016 Hahne, Farina, Jiang and Liebetanz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor 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.
Keywords: 1109 Neurosciences
1702 Cognitive Science
Publication Status: Published
Article Number: 114
Appears in Collections:Bioengineering
Faculty of Engineering