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

Mumtaz, W. and Xia, L. and Malik, A.S. and Mohd Yasin, M.A. (2013) EEG classification of physiological conditions in 2D/3D environments using neural network. In: UNSPECIFIED.

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

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. © 2013 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 6; Conference of 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 ; Conference Date: 3 July 2013 Through 7 July 2013; Conference Code:100170
Uncontrolled Keywords: Approximate entropy; Classification accuracy; Decision variables; EEG classification; Hjorth parameters; Nonlinear features; Permutation entropy; Physiological condition, Entropy; Fractal dimension; Physiology; Three dimensional, Brain computer interface, artificial neural network; brain computer interface; electroencephalography; entropy; environment; fractal analysis; human; language; recreation; signal processing, Brain-Computer Interfaces; Electroencephalography; Entropy; Environment; Fractals; Humans; Language; Neural Networks (Computer); Signal Processing, Computer-Assisted; Video Games
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:51
Last Modified: 09 Nov 2023 15:51
URI: https://khub.utp.edu.my/scholars/id/eprint/3387

Actions (login required)

View Item
View Item