Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion

被引：0

作者：

Szczuko, Piotr ^{[1
]}

机构：

[1] Gdansk Univ Technol, Fac Elect Telecommun & Informat, Gdansk, Poland

来源：

2016 SIGNAL PROCESSING: ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, AND APPLICATIONS (SPA) | 2016年

关键词：

EEG; signal processing; rough set; classification;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

A rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion. Results are commented and further research is proposed.

引用

页码：34 / 39

页数：6

共 15 条

[1]

Gardener M., 2012, Beginning R: the statistical programming language

[2] PhysioBank, PhysioToolkit, and PhysioNet - Components of a new research resource for complex physiologic signals [J].

Goldberger, AL ;

Amaral, LAN ;

Glass, L ;

Hausdorff, JM ;

Ivanov, PC ;

Mark, RG ;

Mietus, JE ;

Moody, GB ;

Peng, CK ;

Stanley, HE .

CIRCULATION, 2000, 101 (23) :E215-E220

[3]

Jung TP, 2000, PSYCHOPHYSIOLOGY, V37, P163, DOI 10.1017/S0048577200980259

[4]

LEEB R, 2004, P 9 COMP VIS WINT WO, P99

[5]

LEEB R, 2004, P 26 ANN INT C IEEE

[6]

Marple SL, 1999, IEEE T SIGNAL PROCES, V47, P2600, DOI 10.1109/78.782222

[7] Motor imagery and direct brain-computer communication [J].

Pfurtscheller, G ;

Neuper, C .

PROCEEDINGS OF THE IEEE, 2001, 89 (07) :1123-1134

[8]

Riza L. S., 2015, ROUGHSETS DATA ANAL

[9] BCI2000: A general-purpose, brain-computer interface (BCI) system [J].

Schalk, G ;

McFarland, DJ ;

Hinterberger, T ;

Birbaumer, N ;

Wolpaw, JR .

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2004, 51 (06) :1034-1043

[10]

Schalk G., BCI2000 INSTRUMENTAT

← 1 2 →