Electrical impedance myography (EIM) For multi-class prosthetic robot hand control

Younggeol Cho, Pyungkang Kim, Kyung-Soo Kim
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引用次数: 1

Abstract

For a several decades, myoelectric control of robotic prosthesis has used electromyograpy (EMG) as its control input to infer human intention. In this paper, we propose to use impedance change of musculoskeletal system to estimate kinematics change of human hand in prosthesis control based on its several features superior to the EMG as follows: clearer signal with much less noise so is less delay caused by filtering and little change of the signal at stationary state of hand motion. We investigated these features of electrical impedance myography (EIM) through several experiments. The result shows it is only minute change of signal occurs at the stationary pose. Although it is sensitive to the motion of other parts (e.g. elbow), it is surely a promising signal for the control of robotic prosthetic hand.
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电阻抗肌图(EIM)用于多类假肢机器人手部控制
几十年来,机器人假肢的肌电控制一直使用肌电图作为控制输入来推断人的意图。在本文中,我们提出利用肌肉骨骼系统的阻抗变化来估计假肢控制中人手的运动学变化,这是基于肌电图优于肌电图的几个特点:信号更清晰,噪声更小,滤波产生的延迟更小,手部运动静止时信号变化很小。我们通过几个实验研究了电阻抗肌图(EIM)的这些特征。结果表明,在静止姿态下,信号仅发生微小变化。虽然它对其他部位(如肘部)的运动很敏感,但它肯定是一个很有前途的机器人假手控制信号。
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