Investigating principal component analysis for classification of EEG data

Author

Deepa, V Baby ; Thangaraj, P. ; Chitra, S.

Author_Institution

M Kumarasamy Coll. of Eng., Karur, India

fYear

2010

fDate

11-12 June 2010

Firstpage

461

Lastpage

464

Abstract

The communication system that does not depend on the brain´s normal output pathways of peripheral nerves and muscles is known as Brain Computer Interaction (BCI). Therefore, BCI system can provide an augmentative communication method for patients with severe motor disabilities. An Electroencephalogram (EEG) is a recording of the very weak (on the order of 5-100 μV) electrical potentials generated by the brain on the scalp. An EEG is recorded as a potential difference between a signal electrode placed on the scalp and a reference electrode (generally connected to one ear or both ears).

Keywords

brain-computer interfaces; electroencephalography; pattern classification; principal component analysis; EEG data classification; brain computer interaction; brain normal output pathways; electroencephalogram; motor disabilities; peripheral nerves; principal component analysis; signal electrode; Computer peripherals; Ear; Educational institutions; Electrodes; Electroencephalography; Information technology; Muscles; Principal component analysis; Scalp; Vectors; BCI; EEG; PCA; SMO;

fLanguage

English

Publisher

ieee

Conference_Titel

Networking and Information Technology (ICNIT), 2010 International Conference on

Conference_Location

Manila

Print_ISBN

978-1-4244-7579-7

Electronic_ISBN

978-1-4244-7578-0

Type

conf

DOI

10.1109/ICNIT.2010.5508471

Filename

5508471