肌电图
计算机科学
限制
人机交互
动觉学习
手势
电刺激肌肉
面部肌肉
机制(生物学)
信号(编程语言)
虚拟现实
电动机控制
功能性电刺激
忠诚
神经科学
人工智能
对象(语法)
物理医学与康复
刺激
脑-机接口
神经生理学
电动机系统
神经假体
计算机视觉
移动设备
肌肉收缩
假手
支持向量机
高保真
运动技能
腿部肌肉
模拟
手势识别
生物医学工程
作者
Ya Huang,Z W Chen,Jingkun Zhou,Huiling Jia,Lung Chow,Y Zhou,Shengxin Jia,Binbin Zhang,Faheem Ershad,Shubham Patel,Chun Ki Yiu,Yuyu Gao,Qiang Zhang,Xingcan Huang,Jian Li,Kuanming Yao,Guangyao Zhao,Peining Chen,Huisheng Peng,Dong Sun
出处
期刊:Science Advances
[American Association for the Advancement of Science]
日期:2026-04-15
卷期号:12 (16): eaed7673-eaed7673
标识
DOI:10.1126/sciadv.aed7673
摘要
Simultaneous electromyography (EMG) sensing and closed-loop electrical stimulation (ES) could enable interactive muscle training, motor rehabilitation, and kinesthetic feedback. However, current systems often suffer from nonconformal device/skin interfaces, poor wearability, and anatomical variability among users, limiting signal fidelity and stimulation precision. Here, we present a fully wireless, skin-integrated electronic tattoo platform that records high-quality EMG and delivers closed-loop ES through custom drawn-on-skin, conformal electrodes with strong adhesion and high spatial accuracy. The system supports closed-loop muscle interactions across body regions and even between individuals. Machine learning models classify EMG patterns from different hand gestures with >90% accuracy and adapt ES parameters to stimulate specific muscle groups. In a heavy object holding task, users reached the required grip behavior substantially faster than unassisted controls, indicating improved neuromuscular efficiency. This closed-loop framework not only supports personalized muscle control but also supports coordinated activation across multiple sites or users, unlocking possibilities in interactive motor training, remote rehabilitation, and virtual reality environments.
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