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Sökning: id:"swepub:oai:research.chalmers.se:099ddb87-31cb-4f47-8f46-13a90c6f4e48" > Decoding of Multipl...

Decoding of Multiple Wrist and Hand Movements Using a Transient EMG Classifier

D'Accolti, Daniele (författare)
Scuola Superiore Sant'Anna di studi universitari e di perfezionamento (SSSUP),Sant'Anna School of Advanced Studies (SSSUP)
Dejanovic, Katarina (författare)
Scuola Superiore Sant'Anna di studi universitari e di perfezionamento (SSSUP),Sant'Anna School of Advanced Studies (SSSUP)
Cappello, Leonardo (författare)
Scuola Superiore Sant'Anna di studi universitari e di perfezionamento (SSSUP),Sant'Anna School of Advanced Studies (SSSUP)
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Mastinu, Enzo, 1987 (författare)
Scuola Superiore Sant'Anna di studi universitari e di perfezionamento (SSSUP),Sant'Anna School of Advanced Studies (SSSUP)
Ortiz Catalan, Max Jair, 1982 (författare)
Göteborgs universitet,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital
Cipriani, C. (författare)
Scuola Superiore Sant'Anna di studi universitari e di perfezionamento (SSSUP),Sant'Anna School of Advanced Studies (SSSUP)
visa färre...
 (creator_code:org_t)
2023
2023
Engelska.
Ingår i: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - 1558-0210 .- 1534-4320. ; 31, s. 208-217
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • The design of prosthetic controllers by means of neurophysiological signals still poses a crucial challenge to bioengineers. State of the art of electromyographic (EMG) continuous pattern recognition controllers rely on the questionable assumption that repeated muscular contractions produce repeatable patterns of steady-state EMG signals. Conversely, we propose an algorithm that decodes wrist and hand movements by processing the signals that immediately follow the onset of contraction (i.e., the \textit {transient} EMG). We collected EMG data from the forearms of 14 non-amputee and 5 transradial amputee participants while they performed wrist flexion/extension, pronation/supination, and four hand grasps (power, lateral, bi-digital, open). We firstly identified the combination of wrist and hand movements that yielded the best control performance for the same participant (intra-subject classification). Then, we assessed the ability of our algorithm to classify participant data that were not included in the training set (cross-subject classification). Our controller achieved a median accuracy of 96% with non-amputees, while it achieved heterogeneous outcomes with amputees, with a median accuracy of 89%. Importantly, for each amputee, it produced at least one \textit {acceptable} combination of wrist-hand movements (i.e., with accuracy >85%). Regarding the cross-subject classifier, while our algorithm obtained promising results with non-amputees (accuracy up to 80%), they were not as good with amputees (accuracy up to 35%), possibly suggesting further assessments with domain-adaptation strategies. In general, our offline outcomes, together with a preliminary online assessment, support the hypothesis that the transient EMG decoding could represent a viable pattern recognition strategy, encouraging further online assessments.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Annan medicin och hälsovetenskap -- Övrig annan medicin och hälsovetenskap (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Other Medical and Health Sciences -- Other Medical and Health Sciences not elsewhere specified (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

transient EMG
pattern recognition
hand wrist prosthetics
cross-subject classifier
Myoelectric control

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