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Wireless high-resolution surface facial electromyography mask for discrimination of standardized facial expressions in healthy adults

Wired high resolution surface electromyography (sEMG) using gelled electrodes is a standard method for psycho-physiological, neurological and medical research. Despite its widespread use electrode placement is elaborative, time-consuming, and the overall experimental setting is prone to mechanical a...

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Bibliographic Details
Published in:Scientific reports 2024-08, Vol.14 (1), p.19317-10
Main Authors: Funk, Paul F., Levit, Bara, Bar-Haim, Chen, Ben-Dov, Dvir, Volk, Gerd Fabian, Grassme, Roland, Anders, Christoph, Guntinas-Lichius, Orlando, Hanein, Yael
Format: Article
Language:English
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Summary:Wired high resolution surface electromyography (sEMG) using gelled electrodes is a standard method for psycho-physiological, neurological and medical research. Despite its widespread use electrode placement is elaborative, time-consuming, and the overall experimental setting is prone to mechanical artifacts and thus offers little flexibility. Wireless and easy-to-apply technologies would facilitate more accessible examination in a realistic setting. To address this, a novel smart skin technology consisting of wireless dry 16-electrodes was tested. The soft electrode arrays were attached to the right hemiface of 37 healthy adult participants (60% female; 20 to 57 years). The participants performed three runs of a standard set of different facial expression exercises. Linear mixed-effects models utilizing the sEMG amplitudes as outcome measure were used to evaluate differences between the facial movement tasks and runs (separately for every task). The smart electrodes showed specific activation patterns for each of the exercises. 82% of the exercises could be differentiated from each other with very high precision when using the average muscle action of all electrodes. The effects were consistent during the 3 runs. Thus, it appears that wireless high-resolution sEMG analysis with smart skin technology successfully discriminates standard facial expressions in research and clinical settings.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-70205-z