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Recent advances in wearable biophysical sensors for continuous muscle monitoring
1School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518060, China; Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China; National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Shenzhen, 518060, China.
Abstract:
Continuous muscle monitoring is paramount for revealing the dynamics of neuromuscular behaviors including fatigue kinetics, muscle recruitment, coordination strategies, and movement adaptations. This capability is fundamental for advancing neurorehabilitation, injury prevention and human-machine interfaces. Importantly, the drive towards wearable muscle sensors is rapidly expanding the feasibility and scope of continuous monitoring applications. This paper highlights recent advancements in wearable muscle sensors spanning electrical, biomechanical, acoustic, and optical sensing domains. Innovations in soft materials and flexible electronics have enabled the development of skin-conformal sensors achieving high-fidelity signal capture. We demonstrate significant advances including enhanced surface electromyography (sEMG) electrodes, ultra-sensitive strain/pressure sensors for muscle deformation monitoring, miniaturized wearable ultrasound transducers for deep-tissue imaging, and near-infrared spectroscopy (NIRS) devices for muscle oxygenation monitoring. We also examine representative multimodal integrations of these modalities, providing the possibility for unprecedented, comprehensive assessment of muscle function. The challenges and prospects are further put forward, including stable skin-sensor interfaces, energy autonomy for continuous operation, accurate decoding of complex multimodal signals, seamless integration with artificial intelligence (AI)-driven analytics and active intervention. This study provides a comprehensive framework for continuous muscle monitoring techniques, and thus paves the way for advancing clinical diagnostics, rehabilitation, and human-machine interaction.
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