EEG classification of physiological conditions in 2D/3D environments using neural network

Author

Mumtaz, Wajid ; Likun Xia ; Malik, A.S. ; Yasin, Mohd Azhar Mohd

Author_Institution

Centre for Intell. Signal & Imaging (CISIR), Univ. Teknol. PETRONAS, Tronoh, Malaysia

fYear

2013

fDate

3-7 July 2013

Firstpage

4235

Lastpage

4238

Abstract

Higher classification accuracy is more desirable for brain computer interface (BCI) applications. The accuracy can be achieved by appropriate selection of relevant features. In this paper a new scheme is proposed based on six different nonlinear features. These features include Sample entropy (SampEn), Composite permutation entropy index (CPEI), Approximate entropy (ApEn), Fractal dimension (FD), Hurst exponent (H) and Hjorth parameters (complexity and mobility). These features are decision variables for classification of physiological conditions: Eyes Open (EO), Eyes Closed (EC), Game Playing 2D (GP2D), Game playing 3D active (GP3DA) and Game playing 3D passive (GP3DP). Results show that the scheme can successfully classify the conditions with an accuracy of 88.9%.

Keywords

brain-computer interfaces; electroencephalography; entropy; feature extraction; fractals; medical signal processing; neural nets; physiology; signal classification; 2D-3D environments; EEG classification; Hjorth complexity parameter; Hjorth mobility parameter; Hurst exponent; approximate entropy; brain computer interface applications; composite permutation entropy index; electroencephalography; eyes closed physiological condition; eyes open physiological condition; fractal dimension; game playing 2D physiological condition; game playing 3D active physiological condition; game playing 3D passive physiological condition; higher-classification accuracy; neural network; nonlinear features; physiological conditions; relevant feature selection; sample entropy; Biological neural networks; Complexity theory; Electroencephalography; Entropy; Physiology; Three-dimensional displays; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE

Conference_Location

Osaka

ISSN

1557-170X

Type

conf

DOI

10.1109/EMBC.2013.6610480

Filename

6610480