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Flexible surface electrodes targeting biopotential signals from forearm muscles for control of prosthetic hands: Part 2 - Characterization of substrates for strain sensors

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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 investigates the use of stretchable strain sensors as an alternative to the gold standard Ag/AgCl surface electromyography (sEMG) electrodes currently utilised to identify movement intention from a user during common hand gestures. Further building on the research in the companion paper, this study documents a series of strain characterisation experiments undertaken on three conductive textiles, two commercial conductive elastomers and one E-skin elastomer produced on site to determine the linearity of each sensor, along with the magnitude of hysteresis in a single stretch and release cycle, and any creep effects present. Gesture identification testing was performed in vivo on two participants, with the three most effective materials across five hand gestures, to assess the functionality of the materials as biopotential electrodes. For this series of experiments, the electrodes were positioned over the site of greatest strain for each gesture. Using a threshold-crossing paradigm, results demonstrated that a commercially sourced conductive fabric can identify 85% of hand gestures performed. The incorporation of flexible strain sensors in hand prosthetic control systems may further increase functionality of such devices, consequently boosting the quality of life of amputees.

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 2 - Characterization of substrates for strain sensors. IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM (pp. 1025-1030). United States: IEEE.

Parent title

IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM

Volume

2019-July

Pagination

1025-1030

Language

English

RIS ID

139918

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