Online Classification of Transient EMG Patterns for the Control of the Wrist and Hand in a Transradial Prosthesis
Artikel i vetenskaplig tidskrift, 2023

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.

virtual reality

human activity recognition

prosthetic hand

Electromyography

pattern recognition

Författare

Daniele D'Accolti

Scuola Superiore Sant'Anna (SSSUP)

F. Clemente

Prensilia

Scuola Superiore Sant'Anna (SSSUP)

Andrea Mannini

Fondazione Don Carlo Gnocchi Onlus

Enzo Mastinu

Scuola Superiore Sant'Anna (SSSUP)

Max Jair Ortiz Catalan

Center for Bionics and Pain Research

Göteborgs universitet

Sahlgrenska universitetssjukhuset

Chalmers, Elektroteknik, System- och reglerteknik

Christian Cipriani

Scuola Superiore Sant'Anna (SSSUP)

IEEE Robotics and Automation Letters

23773766 (eISSN)

Vol. 8 2 1045-1052

Ämneskategorier

Psykologi (exklusive tillämpad psykologi)

Reglerteknik

Datavetenskap (datalogi)

DOI

10.1109/LRA.2023.3235680

Mer information

Senast uppdaterat

2023-02-17