eprintid: 2681
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/26/81
datestamp: 2023-11-09 15:50:55
lastmod: 2023-11-09 15:50:55
status_changed: 2023-11-09 15:44:03
type: article
metadata_visibility: show
creators_name: Mumtaz, W.
creators_name: Xia, L.
creators_name: Malik, A.S.
creators_name: Yasin, M.A.M.
title: Complexity analysis of EEG data during rest state and visual stimulus
ispublished: pub
keywords: Brain regions; Clinical settings; Complexity analysis; Complexity measures; EEG recording; Game environment; Game playing; Malaysia; Monitoring system; Permutation entropy; Physiological condition; Physiological state; Resting state; Road safety; Sample entropy; Visual stimulus, Brain; Data processing; Entropy; Physiology, Electroencephalography
note: cited By 7; Conference of 19th International Conference on Neural Information Processing, ICONIP 2012 ; Conference Date: 12 November 2012 Through 15 November 2012; Conference Code:93816
abstract: This paper presents an approach to analyze physiological states by observing sample entropy (SampEn) and composite permutation entropy index (CPEI) in the complexity measure of an electroencephalographic (EEG) time series. Three states are observed (eyes closed (EC), eyes open (EO) and game playing) during 2D game environment: the last state is observed during visual stimulus, whereas the rest of them are in resting states. This analysis provides an insight into EEG data for frontal, parietal, occipital, temporal and central regions. The results show a clear discrimination among physiological conditions based on values of SampEn and CPEI in the brain regions. The physiological states discrimination based on EEG recordings may be performed in clinical settings. In addition, based on the discovery, a real-time time monitoring system is being developed for the road safety issue by observing vehicle drivers' activity and motorbikes on the road in Malaysia. © 2012 Springer-Verlag.
date: 2012
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869037256&doi=10.1007%2f978-3-642-34475-6_11&partnerID=40&md5=e48206d2a024bffd8e45e9a7de74c1ce
id_number: 10.1007/978-3-642-34475-6₁₁
full_text_status: none
publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
volume: 7663 L
number: PART 1
place_of_pub: Doha
pagerange: 84-91
refereed: TRUE
isbn: 9783642344749
issn: 03029743
citation:   Mumtaz, W. and Xia, L. and Malik, A.S. and Yasin, M.A.M.  (2012) Complexity analysis of EEG data during rest state and visual stimulus.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7663 L (PART 1).  pp. 84-91.  ISSN 03029743