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Recording and Decoding for Neural Prostheses

机译:神经假体的记录和解码

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This paper reviews technologies and signal processing algorithms for decoding peripheral nerve and electrocorticogram signals to interpret human intent and control prosthetic arms. The review includes a discussion of human motor system physiology and physiological signals that can be used to decode motor intent, electrode technology for acquiring neural data, and signal processing methods including decoders based on Kalman filtering and least-squares regressors. Representative results from human experiments demonstrate the progress that has been made in neural decoding and its potential for developing neuroprosthetic arms that act and feel like natural arms.
机译:本文综述了用于解码周围神经和皮层电图信号以解释人的意图并控制假肢的技术和信号处理算法。这篇综述包括对人类运动系统生理学和生理信号(可用于解码运动意图),电极技术以获取神经数据以及信号处理方法(包括基于卡尔曼滤波和最小二乘回归的解码器)的讨论。人体实验的代表性结果表明,神经解码技术已经取得了进步,并且具有开发出像自然手臂一样动作和感觉到的神经假肢手臂的潜力。

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