A Patterned Mechanical–electrical Coupled Sensing Patch for Multimodal Muscle Function Evaluation

Muscles, the fundamental components supporting all human movement, exhibit various signals upon contraction, including mechanical signals indicating tremors or mechanical deformation and electrical signals responsive to muscle fiber activation. For noninvasive wearable devices, these signals can be measured using surface electromyography (sEMG) and force myography (FMG) techniques, respectively. However, relying on a single source of information is insufficient for a comprehensive evaluation of muscle condition. In order to accurately and effectively evaluate the various states of muscles, it is necessary to integrate sEMG and FMG in a spatiotemporally synchronized manner. This study presents a flexible sensor for multimodal muscle state monitoring, integrating serpentine-structured sEMG electrodes with fingerprint-like FMG sensors into a patch approximately 250 mu m thick. This design achieves a multimodal assessment of muscle conditions while maintaining a compact form factor. A thermo-responsive adhesive hydrogel is incorporated to enhance skin adhesion, improving the signal-to-noise ratio of the sEMG signals (33.07 dB) and ensuring the stability of the FMG sensor during mechanical deformation and tremors. The patterned coupled sensing patch demonstrates its utility in tracking muscular strength, assessing fatigue levels, and discerning features of muscle dysfunction by analyzing the time-domain and frequency-domain characteristics of the mechanical-electrical coupled signals, highlighting its potential application in sports training and rehabilitation monitoring.image A novel patterned mechanical-electrical coupled sensing patch is designed for the simultaneous temporal and spatial acquisition of electrical and mechanical signals in muscle activities, which provides an effective tool for comprehensive multimodal muscle function assessment (muscle strength, fatigue level, and muscle dysfunction) through the complementary time and frequency domain characteristics. image