Decoder design and performance comparison of closed-loop brain machine interface

Jinggao Sun, Jiaxiong Yang, Shuo Wang, Huaicheng Yan
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Abstract

In this paper, the spontaneous motion of the single joint is studied on the basis of the cortical neuron firing activity model, and the working principle of the closed-loop brain machine interface is analyzed from the perspective of control theory. The Kalman filter and artificial neural network are used to design system decoder to replace the spinal cord current in original system. According to the result, the performance of decoder design based on neural network is better than that based on Kalman filter.
闭环脑机接口解码器设计及性能比较
本文在皮质神经元放电活动模型的基础上,研究了单个关节的自发运动,并从控制论的角度分析了闭环脑机接口的工作原理。采用卡尔曼滤波和人工神经网络设计系统解码器,取代原系统中的脊髓电流。结果表明,基于神经网络的解码器设计性能优于基于卡尔曼滤波的解码器设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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