可穿戴设备通过多传感器融合改善上肢肌肉功能，实测显著减少震颤、提升运动范围。
Neurotremor: A wearable Supportive Device for Supporting Upper Limb Muscle Function
- 融合肌电与惯性信号，用轻量模型实时识别动作意图
- 震颤指数下降0.092，运动范围提升12.65%，重复动作增2.99次/分钟
- 低延迟高可靠，适合健康人初步验证，未来可用于患者康复
本文提出一种集成表面肌电（sEMG）、惯性测量单元（IMU）及弯折/力传感器的可穿戴辅助原型，搭载M5StickC与ESP32-S3计算模块。信号经带通与陷波滤波后，在250毫秒窗口内提取均方根、平均幅值、零交叉率及4-12 Hz震颤频段功率等特征，输入INT8量化TensorFlow Lite Micro模型。控制指令受控制屏障函数安全约束，并在游戏化任务中实现轻量个性化。12名健康志愿者完成三项日常生活动作任务的初步评估显示：震颤指数下降0.092（95%置信区间[-0.102, -0.079]），运动范围增加12.65%（[+8.43, +13.89]），重复次数提升2.99次/分钟（[+2.61, +3.35]），肌电中位频率斜率改善0.100 Hz/min（[+0.083, +0.127]）。传感-辅助回路运行于100 Hz，设备端延迟中位数为8.7毫秒，所有会话均完成，无设备相关不良事件。结果表明该嵌入式多传感器融合辅助技术具备可行性，后续将在机构审查委员会监督下开展正式患者研究。
原文摘要 · Abstract (English)
A sensor-fused wearable assistance prototype for upper-limb function (triceps brachii and extensor pollicis brevis) is presented. The device integrates surface electromyography (sEMG), an inertial measurement unit (IMU), and flex/force sensors on an M5StickC plus an ESP32-S3 compute hub. Signals are band-pass and notch filtered; features (RMS, MAV, zero-crossings, and 4-12 Hz tremor-band power) are computed in 250 ms windows and fed to an INT8 TensorFlow Lite Micro model. Control commands are bounded by a control-barrier-function safety envelope and delivered within game-based tasks with lightweight personalization. In a pilot technical feasibility evaluation with healthy volunteers (n = 12) performing three ADL-oriented tasks, tremor prominence decreased (Delta TI = -0.092, 95% CI [-0.102, -0.079]), range of motion increased (+12.65%, 95% CI [+8.43, +13.89]), repetitions rose (+2.99 min^-1, 95% CI [+2.61, +3.35]), and the EMG median-frequency slope became less negative (Delta = +0.100 Hz/min, 95% CI [+0.083, +0.127]). The sensing-to-assist loop ran at 100 Hz with 8.7 ms median on-device latency, 100% session completion, and 0 device-related adverse events. These results demonstrate technical feasibility of embedded, sensor-fused assistance for upper-limb function; formal patient studies under IRB oversight are planned.
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