A survey of analysis and classification of EEG signals for brain-computer interfaces

Author

Ilyas, Mohd Zaizu ; Saad, Puteh ; Ahmad, Muhammad Imran

Author_Institution

Embedded, Network, Computing Research Cluster (ENAC) School of Computer and Communication Engineering, Universiti Malaysia Perlis (UniMAP) Kampus Tetap Pauh, 02600 Arau, Perlis, Malaysia

fYear

2015

fDate

30-31 March 2015

Firstpage

1

Lastpage

6

Abstract

A Brain Computer-Interfaces (BCI) is a communication system that enables human brain to interact with machines or devices without involving physical contact by using EEG signals generated from brain activity. Selection of the processing technique of the EEG signals at each processing stage is very important to get the robust BCI system. The aim of this paper is to address the various techniques applied for BCI at each stage such as pre-processing, feature extraction and classification stage. This paper discussed the advantages, disadvantages and current trends of BCI at each stage. Finally, the initial experiment result at each BCI stage was discussed at the end of this paper which is different with previous survey paper.

Keywords

Adaptive filters; Brain; Digital filters; Electroencephalography; Feature extraction; Principal component analysis; Support vector machines; Brain computer-interfaces; classification; electroencephalography(EEG); feature extractiong; pre-processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering (ICoBE), 2015 2nd International Conference on

Conference_Location

Penang, Malaysia

Type

conf

DOI

10.1109/ICoBE.2015.7235129

Filename

7235129