Decoding of Individuated Finger Movements Using Surface Electromyography
Decoding of Individuated Finger Movements Using Surface Electromyography
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DOI：
10.1109/tbme.2008.2005485
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发表时间：
2009-05-01
影响因子：
4.6
通讯作者：
Thakor, Nitish V.
中科院分区：
文献类型：
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作者：
Tenore, Francesco V. G.;Ramos, Ander;Thakor, Nitish V.
上肢假肢在形式和功能上越来越像他们试图取代的肢体，包括多指手和手腕的设计和开发。因此，有必要控制个性化手指运动所需的大量自由度（DOF），优选地使用非侵入性信号。虽然现有的控制范例通常用于驱动基于单自由度钩的配置，但灵巧的任务（诸如单个手指移动）将需要更精细的控制方案。我们表明，它是可以解码的每个手指（10个动作）的个人屈曲和伸展运动的准确性超过90%的transradial截肢者仅使用非侵入性表面肌电信号。此外，经桡动脉截肢者和健全受试者的解码准确性比较显示，这些受试者之间没有统计学显著差异（p < 0.05）。这些结果是令人鼓舞的发展的实时控制策略的基础上的表面肌电信号控制灵巧假手。
Upper limb prostheses are increasingly resembling the limbs they seek to replace in both form and functionality, including the design and development of multifingered hands and wrists. Hence, it becomes necessary to control large numbers of degrees of freedom (DOFs), required for individuated finger movements, preferably using noninvasive signals. While existing control paradigms are typically used to drive a single-DOF hook-based configurations, dexterous tasks such as individual finger movements would require more elaborate control schemes. We show that it is possible to decode individual flexion and extension movements of each finger (ten movements) with greater than 90% accuracy in a transradial amputee using only noninvasive surface myoelectric signals. Further, comparison of decoding accuracy from a transradial amputee and able-bodied subjects shows no statistically significant difference (p < 0.05) between these subjects. These results are encouraging for the development of real-time control strategies based on the surface myoelectric signal to control dexterous prosthetic hands.