EEG based automatic left-right hand movement classification

Author

Fei Wang ; Kijun Kim ; Shiguang Wen ; Yuzhong Zhang ; Chengdong Wu

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China

fYear

2012

fDate

23-25 May 2012

Firstpage

1469

Lastpage

1472

Abstract

As a research focus in bio-rehabilitation field, Brain-Computer Interface that can efficiently improve or recover self-care ability of disabled people has obtained fast development in recent years. In this paper, the phenomenon of event-related de-synchronization in EEG was pre-processed and features were extracted by using common space pattern filtering algorithm. Higher classification accuracy was then obtained by employing C-SVM for left-right hand movement discrimination. Since the effectiveness and simplicity of the proposed scheme, it can be used as an on-line classification algorithm in BCI system.

Keywords

brain-computer interfaces; electroencephalography; feature extraction; filtering theory; health care; medical signal processing; patient rehabilitation; signal classification; support vector machines; synchronisation; BCI system; C-SVM; EEG based automatic left-right hand movement classification; biorehabilitation field; brain-computer interface; classification accuracy; common space pattern filtering algorithm; disabled people; event-related desynchronization; feature extraction; online classification algorithm; self-care ability; Accuracy; Classification algorithms; Electroencephalography; Feature extraction; Filtering algorithms; Mathematical model; Support vector machines; BCI; CSP filtering; EEG; Event-related de-synchronization; Left-right hand movement classification; SVM;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2012 24th Chinese

Conference_Location

Taiyuan

Print_ISBN

978-1-4577-2073-4

Type

conf

DOI

10.1109/CCDC.2012.6244236

Filename

6244236