Long-term decoding of movement force and direction with a wireless myoelectric implant.
Identifieur interne : 000155 ( Main/Exploration ); précédent : 000154; suivant : 000156Long-term decoding of movement force and direction with a wireless myoelectric implant.
Auteurs : Pierre Morel [Allemagne] ; Enrico Ferrea ; Bahareh Taghizadeh-Sarshouri ; Josep Marcel Cardona Audí ; Roman Ruff ; Klaus-Peter Hoffmann ; Sören Lewis ; Michael Russold ; Hans Dietl ; Lait Abu-Saleh ; Dietmar Schroeder ; Wolfgang Krautschneider ; Thomas Meiners ; Alexander GailSource :
- Journal of neural engineering [ 1741-2552 ] ; 2016.
Abstract
The ease of use and number of degrees of freedom of current myoelectric hand prostheses is limited by the information content and reliability of the surface electromyography (sEMG) signals used to control them. For example, cross-talk limits the capacity to pick up signals from small or deep muscles, such as the forearm muscles for distal arm amputations, or sites of targeted muscle reinnervation (TMR) for proximal amputations. Here we test if signals recorded from the fully implanted, induction-powered wireless Myoplant system allow long-term decoding of continuous as well as discrete movement parameters with better reliability than equivalent sEMG recordings. The Myoplant system uses a centralized implant to transmit broadband EMG activity from four distributed bipolar epimysial electrodes.
DOI: 10.1088/1741-2560/13/1/016002
PubMed: 26643959
Affiliations:
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Schroeder</name></author><author><name sortKey="Krautschneider, Wolfgang" sort="Krautschneider, Wolfgang" uniqKey="Krautschneider W" first="Wolfgang" last="Krautschneider">Wolfgang Krautschneider</name></author><author><name sortKey="Meiners, Thomas" sort="Meiners, Thomas" uniqKey="Meiners T" first="Thomas" last="Meiners">Thomas Meiners</name></author><author><name sortKey="Gail, Alexander" sort="Gail, Alexander" uniqKey="Gail A" first="Alexander" last="Gail">Alexander Gail</name></author></analytic><series><title level="j">Journal of neural engineering</title><idno type="eISSN">1741-2552</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The ease of use and number of degrees of freedom of current myoelectric hand prostheses is limited by the information content and reliability of the surface electromyography (sEMG) signals used to control them. For example, cross-talk limits the capacity to pick up signals from small or deep muscles, such as the forearm muscles for distal arm amputations, or sites of targeted muscle reinnervation (TMR) for proximal amputations. Here we test if signals recorded from the fully implanted, induction-powered wireless Myoplant system allow long-term decoding of continuous as well as discrete movement parameters with better reliability than equivalent sEMG recordings. 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