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Synergy matrices to extract fluid wrist motion intents via surface electromyography

机译:通过表面肌电图提取手腕运动意图的协同矩阵

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This paper presented an estimation method of multi-directional and proportional fluid wrist motion intents via sEMG using a non-negative muscle synergy matrix and a joint synergy matrix. A real-time experiment was performed to validate feasibility of the proposed method, and the experimental environment was realized for the individuals with wrist amputation. Only four wrist movements were predefined (wrist extension, wrist flexion, radial deviation, and ulnar deviation), but the experimental results showed that fluid wrist motion intents (e.g. a combination of wrist extension and ulnar deviation) could be extracted. This work could be useful for the people with wrist amputations to restore their wrist functions using myoelectric powered wrist prosthesis, and also for research to investigate how humans learn myoelectric controls in two-dimensions via training.
机译:本文提出了使用非负性肌肉协同矩阵和关节协同矩阵通过sEMG进行的多方向和比例流体腕部运动意图的估计方法。进行了实时实验以验证该方法的可行性,并为手腕截肢的个体提供了实验环境。仅预定义了四个腕部运动(腕部伸展,腕部弯曲,径向偏移和尺骨偏移),但实验结果表明可以提取出腕部活动的意图(例如,腕部延伸和尺骨偏移的组合)。这项工作对于有截肢手术的人使用肌电手腕假体恢复手腕功能可能是有用的,对于研究人类如何通过训练学习二维肌电控制的研究也可能有用。

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