Low-Power Wireless Multi-Channel Surface Electromyography Sensor for Facial Muscle Sensing

Today's electromyography (EMG) sensor systems usually require complicated setups for data acquisition and processing. Especially for facial muscle sensing, small and portable systems are required to allow longer and more realistic measurements. Research in the area of affective states and distinct emotions requires larger studies with extended recording times. Therefore, the acceptance of the sensor by the subjects is crucial. In collaboration with a team of clinical psychologists, this work presents a Bluetooth Low Energy 5.4 enabled wireless surface EMG sensor with edge pre-processing and post-processing on a PC for data evaluation.

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Publication Details

Published
2025-04-14
DOI
https://doi.org/10.1109/wamicon64429.2025.11004086
Primary Topic
Wireless Body Area Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

Low-Power Wireless Multi-Channel Surface Electromyography Sensor for Facial Muscle Sensing

Lena Schindler‐Gmelch, Matthias Berking, Samira Balbach, Amelie Hagelauer et al.
Wireless Body Area Networks
article

Low-Power Wireless Multi-Channel Surface Electromyography Sensor for Facial Muscle Sensing

Lena Schindler‐Gmelch, Matthias Berking, Samira Balbach, Amelie Hagelauer, Christian Dorn
article en

Abstract

Today's electromyography (EMG) sensor systems usually require complicated setups for data acquisition and processing. Especially for facial muscle sensing, small and portable systems are required to allow longer and more realistic measurements. Research in the area of affective states and distinct emotions requires larger studies with extended recording times. Therefore, the acceptance of the sensor by the subjects is crucial. In collaboration with a team of clinical psychologists, this work presents a Bluetooth Low Energy 5.4 enabled wireless surface EMG sensor with edge pre-processing and post-processing on a PC for data evaluation.

Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Technical University of Munich (DE)
Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 90%
Wireless Body Area Networks
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