Literature DB >> 22255044

Wireless dry EEG for drowsiness detection.

Joon Park1, Ling Xu, Vishnu Sridhar, Mike Chi, Gert Cauwenberghs.   

Abstract

Fatigue is a well recognized safety concern for drivers and other industrial workers who must stay alert and attentive for long periods of time. Currently, drowsiness detectors using EEG technology exist but are cumbersome and unreliable. The large number of standard EEG channels requires extensive wiring, while the conventional wet electrodes cause discomfort in long-term monitoring. We propose a simple and cheap one-channel drowsiness detection technology suitable for detecting drowsiness in a variety of environments. Our design incorporates pronged dry-AgCl electrodes in a headband harness, which eliminates the discomfort of gel electrodes while obtaining strong signals from hair covered areas of the scalp. The electrodes send signals to a wireless base unit which then transfers the signal to a computer where it is analyzed using an unique algorithm. With solely this one-channel system, we obtained strong EEG signals from which alpha, beta and theta waves can be observed.

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Year:  2011        PMID: 22255044     DOI: 10.1109/IEMBS.2011.6090895

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Classification of single-trial auditory events using dry-wireless EEG during real and motion simulated flight.

Authors:  Daniel E Callan; Gautier Durantin; Cengiz Terzibas
Journal:  Front Syst Neurosci       Date:  2015-02-17

Review 2.  Electroencephalogram-Based Approaches for Driver Drowsiness Detection and Management: A Review.

Authors:  Gang Li; Wan-Young Chung
Journal:  Sensors (Basel)       Date:  2022-01-31       Impact factor: 3.576

  2 in total

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