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Online Classification of Transient EMG Patterns for the Control of the Wrist and Hand in a Transradial Prosthesis

D'Accolti, D. (author)
Clemente, F. (author)
Mannini, A. (author)
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Mastinu, E. (author)
Ortiz-Catalan, Max Jair, 1982 (author)
Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för ortopedi,Institute of Clinical Sciences, Department of Orthopaedics
Cipriani, C. (author)
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 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2023
2023
English.
In: IEEE Robotics and Automation Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2377-3766 .- 2377-3774. ; 8:2, s. 1045-1052
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Decoding human motor intentions by processing electrophysiological signals is a crucial, yet unsolved, challenge for the development of effective upper limb prostheses. Pattern recognition of continuous myoelectric (EMG) signals represents the state-of-art for multi-DoF prosthesis control. However, this approach relies on the unreliable assumption that repeatable muscular contractions produce repeatable patterns of steady-state EMGs. Here, we propose an approach for decoding wrist and hand movements by processing the signals associated with the onset of contraction (transient EMG). Specifically, we extend the concept of a transient EMG controller for the control of both wrist and hand, and tested it online. We assessed it with one transradial amputee and 15 non-amputees via the Target Achievement Control test. Non-amputees successfully completed 95% of the trials with a median completion time of 17 seconds, showing a significant learning trend (p < 0.001). The transradial amputee completed about the 80% of the trials with a median completion time of 26 seconds. Although the performance proved comparable with earlier studies, the long completion times suggest that the current controller is not yet clinically viable. However, taken collectively, our outcomes reinforce earlier hypothesis that the transient EMG could represent a viable alternative to steady-state pattern recognition approaches.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Medicinteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Medical Engineering (hsv//eng)

Keyword

Electromyography
Wrist
Transient analysis
Prosthetics
Muscles
Training
Electrodes
human activity recognition
pattern recognition
prosthetic hand
virtual reality

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ref (subject category)
art (subject category)

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By the author/editor
D'Accolti, D.
Clemente, F.
Mannini, A.
Mastinu, E.
Ortiz-Catalan, M ...
Cipriani, C.
About the subject
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Medical Engineer ...
Articles in the publication
IEEE Robotics an ...
By the university
University of Gothenburg

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