Advanced EEG processing for the detection of drowsiness in drivers

Griet Goovaerts; Ad Denissen; Milica Milosevic; Geert van Boxtel; Sabine Van Huffel

Advanced EEG processing for the detection of drowsiness in drivers

Griet Goovaerts, Ad Denissen, Milica Milosevic, Geert van Boxtel, Sabine Van Huffel

Signal Processing Systems

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

9 Citations (Scopus)

Abstract

Drowsiness is a serious problem for drivers which causes many accidents every day. It is estimated that drowsiness is the cause of four deaths and 100 injuries per day in the United States. In this paper two methods have been developed to detect drowsiness based on features of ocular artifacts in EEG signals. The ocular artifacts are derived from the EEG signals by using Canonical Correlation Analysis (BSS-CCA). Wavelet transforms are used to automatically select components containing eye blinks. Sixteen features are then calculated from the eye blink and used for drowsiness detection. The first method is based on linear regression, the second on fuzzy detection. For the first method, the drowsiness level is correctly detected in 72% of the epochs. The second method uses fuzzy detection and detects the drowsiness correctly in 65% of the epochs. The best results are obtained when using one single eye blink feature.

Original language	English
Title of host publication	BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014
Publisher	SciTePress Digital Library
Pages	205-212
Number of pages	8
ISBN (Print)	9789897580116
Publication status	Published - 1 Jan 2014
Event	7th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014 - Angers, Loire Valley, France Duration: 3 Mar 2014 → 6 Mar 2014

Conference

Conference	7th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014
Country/Territory	France
City	Angers, Loire Valley
Period	3/03/14 → 6/03/14

Keywords

Blind Source Separation
Drowsiness Detection
EEG

Cite this

Goovaerts, G., Denissen, A., Milosevic, M., van Boxtel, G., & Van Huffel, S. (2014). Advanced EEG processing for the detection of drowsiness in drivers. In BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014 (pp. 205-212). SciTePress Digital Library.

Goovaerts, Griet ; Denissen, Ad ; Milosevic, Milica et al. / Advanced EEG processing for the detection of drowsiness in drivers. BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress Digital Library, 2014. pp. 205-212

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title = "Advanced EEG processing for the detection of drowsiness in drivers",

abstract = "Drowsiness is a serious problem for drivers which causes many accidents every day. It is estimated that drowsiness is the cause of four deaths and 100 injuries per day in the United States. In this paper two methods have been developed to detect drowsiness based on features of ocular artifacts in EEG signals. The ocular artifacts are derived from the EEG signals by using Canonical Correlation Analysis (BSS-CCA). Wavelet transforms are used to automatically select components containing eye blinks. Sixteen features are then calculated from the eye blink and used for drowsiness detection. The first method is based on linear regression, the second on fuzzy detection. For the first method, the drowsiness level is correctly detected in 72\% of the epochs. The second method uses fuzzy detection and detects the drowsiness correctly in 65\% of the epochs. The best results are obtained when using one single eye blink feature.",

keywords = "Blind Source Separation, Drowsiness Detection, EEG",

author = "Griet Goovaerts and Ad Denissen and Milica Milosevic and \{van Boxtel\}, Geert and \{Van Huffel\}, Sabine",

year = "2014",

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booktitle = "BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014",

publisher = "SciTePress Digital Library",

note = "7th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014 ; Conference date: 03-03-2014 Through 06-03-2014",

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Goovaerts, G, Denissen, A, Milosevic, M, van Boxtel, G & Van Huffel, S 2014, Advanced EEG processing for the detection of drowsiness in drivers. in BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress Digital Library, pp. 205-212, 7th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014, Angers, Loire Valley, France, 3/03/14.

Advanced EEG processing for the detection of drowsiness in drivers. / Goovaerts, Griet; Denissen, Ad; Milosevic, Milica et al.
BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress Digital Library, 2014. p. 205-212.

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

TY - GEN

T1 - Advanced EEG processing for the detection of drowsiness in drivers

AU - Goovaerts, Griet

AU - Denissen, Ad

AU - Milosevic, Milica

AU - van Boxtel, Geert

AU - Van Huffel, Sabine

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Drowsiness is a serious problem for drivers which causes many accidents every day. It is estimated that drowsiness is the cause of four deaths and 100 injuries per day in the United States. In this paper two methods have been developed to detect drowsiness based on features of ocular artifacts in EEG signals. The ocular artifacts are derived from the EEG signals by using Canonical Correlation Analysis (BSS-CCA). Wavelet transforms are used to automatically select components containing eye blinks. Sixteen features are then calculated from the eye blink and used for drowsiness detection. The first method is based on linear regression, the second on fuzzy detection. For the first method, the drowsiness level is correctly detected in 72% of the epochs. The second method uses fuzzy detection and detects the drowsiness correctly in 65% of the epochs. The best results are obtained when using one single eye blink feature.

AB - Drowsiness is a serious problem for drivers which causes many accidents every day. It is estimated that drowsiness is the cause of four deaths and 100 injuries per day in the United States. In this paper two methods have been developed to detect drowsiness based on features of ocular artifacts in EEG signals. The ocular artifacts are derived from the EEG signals by using Canonical Correlation Analysis (BSS-CCA). Wavelet transforms are used to automatically select components containing eye blinks. Sixteen features are then calculated from the eye blink and used for drowsiness detection. The first method is based on linear regression, the second on fuzzy detection. For the first method, the drowsiness level is correctly detected in 72% of the epochs. The second method uses fuzzy detection and detects the drowsiness correctly in 65% of the epochs. The best results are obtained when using one single eye blink feature.

KW - Blind Source Separation

KW - Drowsiness Detection

KW - EEG

UR - https://www.scopus.com/pages/publications/84902338956

M3 - Conference contribution

AN - SCOPUS:84902338956

SN - 9789897580116

SP - 205

EP - 212

BT - BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014

PB - SciTePress Digital Library

T2 - 7th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014

Y2 - 3 March 2014 through 6 March 2014

ER -

Goovaerts G, Denissen A, Milosevic M, van Boxtel G, Van Huffel S. Advanced EEG processing for the detection of drowsiness in drivers. In BIOSIGNALS 2014 - 7th Int. Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 7th Int. Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress Digital Library. 2014. p. 205-212

Advanced EEG processing for the detection of drowsiness in drivers

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