可穿戴计算机
计算机科学
肌电图
机器人学
压力传感器
可穿戴技术
康复机器人
人工智能
肌肉疲劳
联轴节(管道)
工作(物理)
机器人
生物医学工程
神经假体
机械系统
极限(数学)
计算机视觉
材料科学
数据采集
康复
信号(编程语言)
功能性电刺激
电生理学
神经工程
人工肌肉
软机器人
人机交互
机械设计
作者
Peng Wang,Jixiao Liu,Song Gao,Funing Hou,Cong Ma,Cuiyuan Liang,Longlong Cui,Dianpeng Qi,Shijie Guo
标识
DOI:10.1002/adhm.202504778
摘要
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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