Classification of driver fatigue in an electroencephalography-based countermeasure system with source separation module

Rifai Chai, Ganesh R. Naik, Yvonne Tran, Sai Ho Ling, Ashley Craig, Hung T. Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

An electroencephalography (EEG)-based counter measure device could be used for fatigue detection during driving. This paper explores the classification of fatigue and alert states using power spectral density (PSD) as a feature extractor and fuzzy swarm based-artificial neural network (ANN) as a classifier. An independent component analysis of entropy rate bound minimization (ICA-ERBM) is investigated as a novel source separation technique for fatigue classification using EEG analysis. A comparison of the classification accuracy of source separator versus no source separator is presented. Classification performance based on 43 participants without the inclusion of the source separator resulted in an overall sensitivity of 71.67%, a specificity of 75.63% and an accuracy of 73.65%. However, these results were improved after the inclusion of a source separator module, resulting in an overall sensitivity of 78.16%, a specificity of 79.60% and an accuracy of 78.88% (p < 0.05).

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan
Place of PublicationMilan
Pages514-517
Number of pages4
ISBN (Electronic)9781424492718, 9781424492701
DOIs
Publication statusPublished - 5 Nov 2015
Externally publishedYes
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Milan, Italy
Duration: 25 Aug 201529 Aug 2015
Conference number: 37
https://ieeexplore.ieee.org/xpl/conhome/7302811/proceeding

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated titleEMBC 2015
CountryItaly
CityMilan
Period25/08/1529/08/15
Internet address

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  • Cite this

    Chai, R., Naik, G. R., Tran, Y., Ling, S. H., Craig, A., & Nguyen, H. T. (2015). Classification of driver fatigue in an electroencephalography-based countermeasure system with source separation module. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan (pp. 514-517). https://doi.org/10.1109/EMBC.2015.7318412