Vigilance differentiation from EEG complexity attributes

Junhua Li; Indu Prasad; Justin Dauwels; Nitish V. Thakor; Hasan Ai-Nashash

doi:10.1007/978-3-319-26561-2_24

Vigilance differentiation from EEG complexity attributes

Junhua Li, Indu Prasad, Justin Dauwels, Nitish V. Thakor, Hasan Ai-Nashash

School of Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Vigilance is an ability to maintain concentrated attention on a particular event or target stimulus. Monitoring tasks require certainly high vigilance to properly detect rare occurrence or accurately respond to stimulation. Changes in vigilance can be reflected by EEG signal, so vigilance levels can be classified based on features extracted from EEG. Up to now, power spectral density was commonly employed as features to differentiate between vigilance levels in majority of previous studies. To the best of our knowledge, multifractal attributes for vigilance differentiation have not been exploited, and their feasibility still need to be investigated. In this study, we first extracted multifractal attributes based on wavelet leaders, and then selected statistically significant distinct attributes for the following classification (two vigilance levels). According to the results, classification accuracy was improved with increase of time window used for feature extraction. When time window was increased to 50 s, an averaged accuracy of 91.67% was achieved, and accuracies for all subjects were higher than 85 %. Our results suggest that multifractal attributes are promising for vigilance differentiation.

Original language	English (US)
Title of host publication	Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
Editors	Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu
Publisher	Springer Verlag
Pages	199-206
Number of pages	8
ISBN (Print)	9783319265605
DOIs	https://doi.org/10.1007/978-3-319-26561-2_24
State	Published - 2015
Event	22nd International Conference on Neural Information Processing, ICONIP 2015 - Istanbul, Turkey Duration: Nov 9 2015 → Nov 12 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9492
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	22nd International Conference on Neural Information Processing, ICONIP 2015
Country/Territory	Turkey
City	Istanbul
Period	11/9/15 → 11/12/15

Keywords

Complexity attribute
Feature selection
Self-similarity
Sustained attention
Vigilance classification

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-26561-2_24

Cite this

Li, J., Prasad, I., Dauwels, J., Thakor, N. V., & Ai-Nashash, H. (2015). Vigilance differentiation from EEG complexity attributes. In S. Arik, T. Huang, W. K. Lai, & Q. Liu (Eds.), Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings (pp. 199-206). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9492). Springer Verlag. https://doi.org/10.1007/978-3-319-26561-2_24

Vigilance differentiation from EEG complexity attributes. / Li, Junhua; Prasad, Indu; Dauwels, Justin et al.
Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. ed. / Sabri Arik; Tingwen Huang; Weng Kin Lai; Qingshan Liu. Springer Verlag, 2015. p. 199-206 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9492).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, J, Prasad, I, Dauwels, J, Thakor, NV & Ai-Nashash, H 2015, Vigilance differentiation from EEG complexity attributes. in S Arik, T Huang, WK Lai & Q Liu (eds), Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9492, Springer Verlag, pp. 199-206, 22nd International Conference on Neural Information Processing, ICONIP 2015, Istanbul, Turkey, 11/9/15. https://doi.org/10.1007/978-3-319-26561-2_24

Li J, Prasad I, Dauwels J, Thakor NV, Ai-Nashash H. Vigilance differentiation from EEG complexity attributes. In Arik S, Huang T, Lai WK, Liu Q, editors, Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. Springer Verlag. 2015. p. 199-206. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-26561-2_24

Li, Junhua ; Prasad, Indu ; Dauwels, Justin et al. / Vigilance differentiation from EEG complexity attributes. Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings. editor / Sabri Arik ; Tingwen Huang ; Weng Kin Lai ; Qingshan Liu. Springer Verlag, 2015. pp. 199-206 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Vigilance differentiation from EEG complexity attributes

Abstract

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Keywords

ASJC Scopus subject areas

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