用织物电极捕捉拇指内在肌电信号，助力中风康复设备更精准控制。
Fabric Sensing of Intrinsic Hand Muscle Activity
- 采用织物电极制成柔性传感袖套，贴合手掌无负担。
- 在孤立与等长收缩测试中成功识别拇指动作与肌电活动。
- 适合康复机器人、可穿戴设备开发者参考应用。
可穿戴机器人有望帮助中风患者恢复手部功能。现有基于表面肌电（sEMG）控制的设备多依赖前臂的外在肌肉信号，因电极易于放置且不干扰手部动作。本文聚焦于位于皮肤表层的拇指内在肌，其信号理论上更易通过sEMG获取。然而传统刚性电极无法直接置于手部，会增加体积并影响功能。为此，我们提出一种新型织物传感袖套，利用纺织电极测量拇指内在肌肉的sEMG信号。在独立及等长收缩条件下评估了该袖套对拇指运动和肌电活动的检测性能。结果表明，基于织物的传感器可作为低成本、轻量化、非侵入式替代方案，适用于可穿戴机器人系统。
原文摘要 · Abstract (English)
Wearable robotics have the capacity to assist stroke survivors in assisting and rehabilitating hand function. Many devices that use surface electromyographic (sEMG) for control rely on extrinsic muscle signals, since sEMG sensors are relatively easy to place on the forearm without interfering with hand activity. In this work, we target the intrinsic muscles of the thumb, which are superficial to the skin and thus potentially more accessible via sEMG sensing. However, traditional, rigid electrodes can not be placed on the hand without adding bulk and affecting hand functionality. We thus present a novel sensing sleeve that uses textile electrodes to measure sEMG activity of intrinsic thumb muscles. We evaluate the sleeve's performance on detecting thumb movements and muscle activity during both isolated and isometric muscle contractions of the thumb and fingers. This work highlights the potential of textile-based sensors as a low-cost, lightweight, and non-obtrusive alternative to conventional sEMG sensors for wearable robotics.
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