A portable device for real time drowsiness detection using novel active dry electrode system

Pai Yuan Tsai; Weichih Hu; Terry B J Kuo; Liang Yu Shyu

doi:10.1109/IEMBS.2009.5334491

A portable device for real time drowsiness detection using novel active dry electrode system

Pai Yuan Tsai, Weichih Hu, Terry B J Kuo, Liang Yu Shyu

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

45 Citations (Scopus)

Abstract

Electroencephalogram (EEG) signals give important information about the vigilance states of a subject. Therefore, this study constructs a real-time EEG-based system for detecting a drowsy driver. The proposed system uses a novel six channels active dry electrode system to acquire EEG non-invasively. In addition, it uses a TMS320VC5510 DSP chip as the algorithm processor, and a MSP430F149 chip as a controller to achieve a real-time portable system. This study implements stationary wavelet transform to extract two features of EEG signal: integral of EEG and zero crossings as the input to a back propagation neural network for vigilance states classification. This system can discriminate alertness and drowsiness in real-time. The accuracy of the system is 79.1%for alertness and 90.91% for drowsiness states. When the system detects drowsiness, it will warn drivers by using a vibrator and a beeper.

Original language	English
Title of host publication	Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication	Engineering the Future of Biomedicine, EMBC 2009
Pages	3775-3778
Number of pages	4
DOIs	https://doi.org/10.1109/IEMBS.2009.5334491
Publication status	Published - 2009
Externally published	Yes
Event	31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States Duration: Sept 2 2009 → Sept 6 2009

Conference

Conference	31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Country/Territory	United States
City	Minneapolis, MN
Period	9/2/09 → 9/6/09

ASJC Scopus subject areas

Cell Biology
Developmental Biology
Biomedical Engineering
Medicine(all)

Access to Document

10.1109/IEMBS.2009.5334491

Cite this

Tsai, P. Y., Hu, W., Kuo, T. B. J., & Shyu, L. Y. (2009). A portable device for real time drowsiness detection using novel active dry electrode system. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 3775-3778). Article 5334491 https://doi.org/10.1109/IEMBS.2009.5334491

A portable device for real time drowsiness detection using novel active dry electrode system. / Tsai, Pai Yuan; Hu, Weichih; Kuo, Terry B J et al.
Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. p. 3775-3778 5334491.

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

Tsai, PY, Hu, W, Kuo, TBJ & Shyu, LY 2009, A portable device for real time drowsiness detection using novel active dry electrode system. in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009., 5334491, pp. 3775-3778, 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, Minneapolis, MN, United States, 9/2/09. https://doi.org/10.1109/IEMBS.2009.5334491

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title = "A portable device for real time drowsiness detection using novel active dry electrode system",

abstract = "Electroencephalogram (EEG) signals give important information about the vigilance states of a subject. Therefore, this study constructs a real-time EEG-based system for detecting a drowsy driver. The proposed system uses a novel six channels active dry electrode system to acquire EEG non-invasively. In addition, it uses a TMS320VC5510 DSP chip as the algorithm processor, and a MSP430F149 chip as a controller to achieve a real-time portable system. This study implements stationary wavelet transform to extract two features of EEG signal: integral of EEG and zero crossings as the input to a back propagation neural network for vigilance states classification. This system can discriminate alertness and drowsiness in real-time. The accuracy of the system is 79.1%for alertness and 90.91% for drowsiness states. When the system detects drowsiness, it will warn drivers by using a vibrator and a beeper.",

author = "Tsai, {Pai Yuan} and Weichih Hu and Kuo, {Terry B J} and Shyu, {Liang Yu}",

year = "2009",

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AB - Electroencephalogram (EEG) signals give important information about the vigilance states of a subject. Therefore, this study constructs a real-time EEG-based system for detecting a drowsy driver. The proposed system uses a novel six channels active dry electrode system to acquire EEG non-invasively. In addition, it uses a TMS320VC5510 DSP chip as the algorithm processor, and a MSP430F149 chip as a controller to achieve a real-time portable system. This study implements stationary wavelet transform to extract two features of EEG signal: integral of EEG and zero crossings as the input to a back propagation neural network for vigilance states classification. This system can discriminate alertness and drowsiness in real-time. The accuracy of the system is 79.1%for alertness and 90.91% for drowsiness states. When the system detects drowsiness, it will warn drivers by using a vibrator and a beeper.

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A portable device for real time drowsiness detection using novel active dry electrode system

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