Electroencephalographic study of drowsiness in simulated driving with sleep deprivation

Eoh, Hong; Chung, Min K.; Kim, Seong Han

doi:10.1016/j.ergon.2004.09.006

Cited by 384 publications

(285 citation statements)

References 22 publications

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“…As these techniques typically average EEG activity over several seconds (up to one minute), detection of brief microsleep episodes, as studied here, would not be possible. Eoh et al (2005) showed that the numbers of short (1 second) alpha bursts and driving incidents increased with driving duration. However, instead of finding bursts occurring at the time of an incident, they noted a drop in alpha + theta/beta power in the seconds after incidents compared to the preceding 10 seconds.…”

Section: Discussionmentioning

confidence: 98%

“…Although we used expert visual inspection of the EEG to identify microsleeps according to generally accepted criteria, this technique is inherently subjective. Several studies have used "quantitative" EEG methods to identify driver sleepiness (de Waard & Brookhuis, 1991;Eoh et al, 2005;Kecklund & Akerstedt, 1993;Horne & Reyner, 1996;Lal & Craig, 2002). Alpha and theta power (usually expressed as the relative power of alpha + theta/beta), and the frequency of alpha and theta bursts typically increase during prolonged driving, and are associated with poor driving performance.…”

Section: Discussionmentioning

confidence: 99%

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Driver performance in the moments surrounding a microsleep

Boyle

Tippin

Paul

et al. 2008

Transportation Research Part F: Traffic Psychology and Behaviou

131

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This study examined if individuals who are at increased risk for drowsy-driving because of obstructive sleep apnea syndrome (OSAS), have impairments in driving performance in the moments during microsleep episodes as opposed to during periods of wakefulness. Twenty-four licensed drivers diagnosed with OSAS based on standard clinical and polysomnographic criteria, participated in an hour-long drive in a high-fidelity driving simulator with synchronous electroencephalographic (EEG) recordings for identification of microsleeps. The drivers showed significant deterioration in vehicle control during the microsleep episodes compared to driving performance in the absence of microsleeps on equivalent segments of roadway. The degree of performance decrement correlated with microsleep duration, particularly on curved roads. Results indicate that driving performance deteriorates during microsleep episodes. Detecting microsleeps in real-time and identifying how these episodes of transition between wakefulness and sleep impair driver performance is relevant to the design and implementation of countermeasures such as drowsy driver detection and alerting systems that use EEG technology.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Driver performance in the moments surrounding a microsleep

Boyle

Tippin

Paul

et al. 2008

Transportation Research Part F: Traffic Psychology and Behaviou

131

View full text Add to dashboard Cite

show abstract

“…In a similar way, we also realized that only a limited number of drowsiness investigations have utilized head-mounted measurement techniques. Driving in a drowsy condition was examined by certain researchers [18,19] using different measurements. Even though the accuracy reached almost 99%, these results were obtained in sleep-deprived subjects rather than under a condition where natural drowsiness occurred.…”

mentioning

confidence: 99%

Gazing Time Analysis for Drowsiness Assessment Using Eye Gaze Tracker

Rumagit¹,

Akbar²,

Igasaki³

2017

TELKOMNIKA

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“…Driver fatigue is a process that involves successive episodes of micro-sleeps, where the subject may go in and out of a fatigue state [6]. EEG has been used in many driver studies conducted in the lab and field [5,[7][8][9][10], and is one of the most reliable indicators of fatigue [11]. Studies have found that EEG has acceptable test and retest reliability [6,[12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…The electroencephalography (EEG), pioneered by Hans Berger, measures the electric potentials on the scalp and provides continuous measure of cortical activity [2,3]. EEG has played an important role due to its non-invasiveness and the capability of long term measurement in the field of epilepsy, sleeping disorder, fatigue, and various neurological conditions [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%