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Flexible surface electrodes targeting biopotential signals from forearm muscles for control of prosthetic hands: Part 1 - Characterisation of semg electrodes

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posted on 2024-11-16, 04:10 authored by Siobhan O'BrienSiobhan O'Brien, Thomas Searle, Gursel AliciGursel Alici
This study is Part 1 of two studies which investigate the use of various flexible surface sensors as an alternative to the gold standard Ag/AgCl surface electromyography (sEMG) electrodes in identifying movement intention from a user during common hand gestures. Three conductive textiles, two commercial conductive elastomers and one E-skin elastomer produced on site were tested as biopotential electrodes to establish the efficacy of each in gathering movement intention from the human brain at the level of the muscle. Testing was performed in vivo on two participants across three hand gestures, with results demonstrating that sEMG electrodes made from a commercially sourced conductive fabric can outperform the traditional Ag/AgCl sEMG electrodes, obtaining substantially larger peak and RMS measurements. Given the disadvantages of Ag/AgCl electrodes over long usage periods, namely their tendency to dry out and significant skin preparation, resulting in variable impedances and skin irritation respectively, the incorporation of flexible surface EMG electrodes in hand prosthetic control systems would increase functionality of the prosthetic devices, consequently increasing the quality of life of prosthetic hand users.

Funding

ARC Centre of Excellence for Electromaterials Science

Australian Research Council

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Citation

O'Brien, S., Searle, T. & Alici, G. (2019). Flexible surface electrodes targeting biopotential signals from forearm muscles for control of prosthetic hands: Part 1 - Characterisation of semg electrodes. IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM (pp. 1019-1024). United States: IEEE.

Parent title

IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM

Volume

2019-July

Pagination

1019-1024

Language

English

RIS ID

139916

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