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

doi:10.1109/EMBC.2015.7318412

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 proceeding › Conference contribution › peer-review

9 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 language	English
Title of host publication	2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan
Place of Publication	Milan
Pages	514-517
Number of pages	4
ISBN (Electronic)	9781424492718, 9781424492701
DOIs	https://doi.org/10.1109/EMBC.2015.7318412
Publication status	Published - 5 Nov 2015
Externally published	Yes
Event	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Milan, Italy Duration: 25 Aug 2015 → 29 Aug 2015 Conference number: 37 https://ieeexplore.ieee.org/xpl/conhome/7302811/proceeding

Conference

Conference	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated title	EMBC 2015
Country/Territory	Italy
City	Milan
Period	25/08/15 → 29/08/15
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7302811/proceeding

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10.1109/EMBC.2015.7318412Licence: In Copyright

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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

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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).",

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Chai, R, Naik, GR, Tran, Y, Ling, SH, Craig, A & Nguyen, HT 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. Milan, pp. 514-517, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Italy, 25/08/15. https://doi.org/10.1109/EMBC.2015.7318412

Classification of driver fatigue in an electroencephalography-based countermeasure system with source separation module. / Chai, Rifai; Naik, Ganesh R.; Tran, Yvonne et al.
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan. Milan, 2015. p. 514-517.

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

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AU - Craig, Ashley

AU - Nguyen, Hung T.

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

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