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 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.

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Publication Details

Journal
Scientific Reports
Published
2024-08-20
DOI
https://doi.org/10.1038/s41598-024-70205-z
Citations
10
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
1.66

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article

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

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10 citations
Scientific Reports
Muscle activation and electromyography studies
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article

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

Roland Graßme, Yael Hanein, Dvir Ben-Dov, Gerd Fabian Volk, Christoph Anders, Bara Levit, Chen Bar-Haim, Orlando Guntinas‐Lichius, Paul F. Funk
article en
10 citations

Abstract

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.

Scientific ReportsVol. 14(1)
Reichman University (IL), Tel Aviv University (IL), Herzliya Medical Center (IL), Jena University Hospital (DE), Friedrich Schiller University Jena (DE)
Friedrich-Schiller-Universität Jena, Deutsche Forschungsgemeinschaft, Israel Science Foundation
Openalex Percentile: Top 17%
Muscle activation and electromyography studies
1.66
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