Wearable Ferroelectret Sensors for Muscle Activity Measurements

Wearable sensors for measuring muscle activity and the resulting limb motion are essential for various applications, including motion analysis, human-machine interaction, and control of assistance systems such as exoskeletons. We examine wearable ferroelectret sensors for force myography (FMG), in particular comparing the FMG data to muscle activity measurements obtained by electromyography (EMG). Muscle activity data were acquired from a participant during walking using pairs of FMG and EMG sensors placed on the vastus medialis and biceps femoris muscles. We analyze activation timing, signal variability, and the effect of different walking speeds on signal amplitude. The FMG sensors prove to be effective in capturing activity patterns similar to those obtained by EMG, with mean absolute errors of 6.1% for the vastus medialis and 18.9% for the biceps femoris. Furthermore, the FMG signals are more consistent across strides, exhibiting less than half the stride-to-stride variability. In conclusion, our ferroelectret sensors for FMG have the potential to increase robustness of muscle activity measurements in applications such as motion analysis and control of wearable robots.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1109/uffc-js60046.2024.10793709
Citations
4
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.74

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article

Wearable Ferroelectret Sensors for Muscle Activity Measurements

Omid Mohseni, André Seyfarth, Omar Ben Dali, Mario Kupnik et al.
4 citations
Advanced Sensor and Energy Harvesting Materials
0.74
article

Wearable Ferroelectret Sensors for Muscle Activity Measurements

Omid Mohseni, André Seyfarth, Omar Ben Dali, Mario Kupnik, Niklas Schäfer, Bastian Latsch, Martin Grimmer, Philipp Beckerle, Julian Seiler, Alexander Anton Altmann, Stephan Schaumann, Steffen Graffe
article en
4 citations

Abstract

Wearable sensors for measuring muscle activity and the resulting limb motion are essential for various applications, including motion analysis, human-machine interaction, and control of assistance systems such as exoskeletons. We examine wearable ferroelectret sensors for force myography (FMG), in particular comparing the FMG data to muscle activity measurements obtained by electromyography (EMG). Muscle activity data were acquired from a participant during walking using pairs of FMG and EMG sensors placed on the vastus medialis and biceps femoris muscles. We analyze activation timing, signal variability, and the effect of different walking speeds on signal amplitude. The FMG sensors prove to be effective in capturing activity patterns similar to those obtained by EMG, with mean absolute errors of 6.1% for the vastus medialis and 18.9% for the biceps femoris. Furthermore, the FMG signals are more consistent across strides, exhibiting less than half the stride-to-stride variability. In conclusion, our ferroelectret sensors for FMG have the potential to increase robustness of muscle activity measurements in applications such as motion analysis and control of wearable robots.

Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Technische Universität Darmstadt (DE)
Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 31%
Advanced Sensor and Energy Harvesting Materials
0.74
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