脑控制瘫痪假肢的最新进展:周五主题演讲

A. Schwartz
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引用次数: 1

摘要

神经元同时对多个参数进行编码,但在单个神经元层面的编码保真度较弱。相比之下,随着对神经群体功能的更好理解,我们现在可以解码复杂的手臂和手的运动。我们已经开发了一种简单的提取算法来捕获手臂运动数据,并显示瘫痪的患者无法移动她的身体的任何部分,她的脖子可以控制高性能的“模块化假肢”同时使用10个自由度。这种假肢的控制直观,动作协调、优美,与自然的手臂和手的运动非常相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recent Advances in Brain-controlled Prosthetics for Paralysis: Friday Keynote
Neurons encode many parameters simultaneously, but the encoding fidelity at the level of individual neurons is weak. In contrast, with a better understanding of neural population function we can now decode complex arm and hand movement. We have developed a simple extraction algorithm to capture arm movement data and shown that a paralyzed patient who cannot move any part of her body below her neck can control a high-performance "modular prosthetic limb" using 10 degrees-of-freedom simultaneously. The control of this artificial limb is intuitive, with coordinated, graceful motion, closely resembling natural arm and hand movement.
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