Recording and Decoding for Neural Prostheses

作     者：Warren, David J. Kellis, Spencer Nieveen, Jacob G. Wendelken, Suzanne M. Dantas, Henrique Davis, Tyler S. Hutchinson, Douglas T. Normann, Richard A. Clark, Gregory A. Mathews, V. John 

作者机构：Univ Utah Dept Bioengn Salt Lake City UT 84112 USA CALTECH Biol & Biol Engn Div Pasadena CA 91125 USA Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA Oregon State Univ Sch Elect Engn & Comp Sci Corvallis OR 97331 USA Univ Utah Dept Neurosurg Salt Lake City UT 84132 USA Univ Utah Dept Orthopaed Surg Salt Lake City UT 84108 USA 

出 版 物：《PROCEEDINGS OF THE IEEE》 (电气与电子工程师学会会报)

年 卷 期：2016年第104卷第2期

页      面：374-391页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：Defense Advanced Research Project Agency (DARPA) [N6600115C4017] Space and Naval Warfare Systems Center Pacific (SSC Pacific) [N66001-15-C-4017] 

主　　题：Brain-computer interface electrocorticogram Kalman decoders neural decoding neuroprosthetics peripheral nerve signals 

摘      要：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.