Hidden Markov models for online classification of single trial EEG data

被引：140

作者：

Obermaier, B ^{[1
]}

Guger, C

Neuper, C

Pfurtscheller, G

机构：

[1] Graz Univ Technol, Inst Biomed Engn, Dept Med Informat, A-8010 Graz, Austria

[2] Graz Univ Technol, Ludwig Boltzmann Inst Med Informat & Neuroinforma, A-8010 Graz, Austria

[3] Inst Super Tecn, ISR, LaSEEB, Lisbon, Portugal

来源：

PATTERN RECOGNITION LETTERS | 2001年 / 22卷 / 12期

基金：

奥地利科学基金会;

关键词：

brain-computer interface (BCI); hidden Markov models; EEG classification; event-related desynchronisation (ERD);

D O I：

10.1016/S0167-8655(01)00075-7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Hidden Markov models (HMMs) are presented for the online classification of single trial EEG data during imagination of a left or right hand movement. The classification shows an improvement of the online experiment and the temporal determination of minimal classification error compared to linear classification methods. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：1299 / 1309

页数：11

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