Dexterous control of a prosthetic hand using fine-wire intramuscular electrodes in targeted extrinsic muscles.

Dexterous control of a prosthetic hand using fine-wire intramuscular electrodes in targeted extrinsic muscles.
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DOI:
10.1109/tnsre.2014.2301234
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发表时间:
2014-07
期刊:
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
影响因子:
--
通讯作者:
ff Weir RF
ff Weir RF
中科院分区:
其他
文献类型:
--
作者:
Cipriani C;Segil JL;Birdwell JA;ff Weir RF

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截肢后恢复相当于人手的灵巧运动功能是康复工程的主要目标之一。为了实现这一目标,需要实现一个轻松的人机界面,将人造手与意志源联系起来。利用神经信号并将其用作神经假体的控制输入的尝试涉及神经肌肉系统中的侵入性和分层位置。然而,今天,临床上可行的主要控制技术是通过表面电极测量外周肌电图。这种方法在生理上既不合适也不灵巧,因为无法获得任意的手指运动或手部姿势。在这里,我们展示了在健康受试者上使用肌内电极直接从前臂肌肉信号实现实时、连续和同步控制多指假肢的可行性。受试者收缩生理上适当的肌肉来独立控制物理机械手手指的四个自由度。受试者将这种控制描述为直观的,并且表现出无需明确训练即可将手驱动成 12 种姿势的能力。这是第一项实时处理周围神经关联并用于以直观和直接的方式同时控制一只手的多个手指的研究。
Restoring dexterous motor function equivalent to that of the human hand after amputation is one of the major goals in rehabilitation engineering. To achieve this requires the implementation of a effortless human–machine interface that bridges the artificial hand to the sources of volition. Attempts to tap into the neural signals and to use them as control inputs for neuroprostheses range in invasiveness and hierarchical location in the neuromuscular system. Nevertheless today, the primary clinically viable control technique is the electromyogram measured peripherally by surface electrodes. This approach is neither physiologically appropriate nor dexterous because arbitrary finger movements or hand postures cannot be obtained. Here we demonstrate the feasibility of achieving real-time, continuous and simultaneous control of a multi-digit prosthesis directly from forearm muscles signals using intramuscular electrodes on healthy subjects. Subjects contracted physiologically appropriate muscles to control four degrees of freedom of the fingers of a physical robotic hand independently. Subjects described the control as intuitive and showed the ability to drive the hand into 12 postures without explicit training. This is the first study in which peripheral neural correlates were processed in real-time and used to control multiple digits of a physical hand simultaneously in an intuitive and direct way.