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A Wearable Multimodal Sensor for Simultaneous and Co-Located Muscle Electrophysiological and Mechanical Monitoring
Peng Wang1, Jixiao Liu1, Song Gao1
1School of Mechanical Engineering, Hebei University of Technology, Tianjin, China.
Abstract:
Simultaneous and spatially aligned acquisition of electrical and mechanical muscle signals is essential to accurately capture neuromechanical coupling between neural activation and mechanical output. However, existing multi-device methods face issues like non-simultaneous recordings, spatial deviation, and complex setups that complicate data collection and compromise integrity. Here, we present a wearable multimodal sensor that simultaneously acquires surface electromyography (sEMG), surface muscle pressure (SMP), and mechanomyography (MMG) at the same location using a single sensing material and integrated structure. This long-term stable system demonstrates high signal-to-noise ratio (SNR, 27.4 dB) and reusability for electrophysiological recordings, along with excellent mechanical performance, including low detection limit (≈25 Pa), broad pressure range (0-320 kPa), and fast response (≈16 ms). System-level validation across exercise, fatigue, and rehabilitation scenarios confirms robust capture of muscle neuromechanical dynamics. This work provides a high-performance yet simplified platform for wearable muscle monitoring, with potential impact in rehabilitation robotics and human-machine interfacing.
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