文献类型：期刊文献

英文题名：Decoder design and performance comparison of closed-loop brain machine interface

作者：Sun, Jinggao[1]; Yang, Jiaxiong[1]; Wang, Shuo[1]; Yan, Huaicheng[1]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China

年份：2017

卷号：2018-January

起止页码：101

外文期刊名：2017 Australian and New Zealand Control Conference, ANZCC 2017

收录：EI(收录号：20183105616853)

语种：英文

外文关键词：Neural networks - Brain - Brain computer interface - Decoding

摘要：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. ? 2017 IEEE.