EEG alpha spindle measures as indicators of driver fatigue under real traffic conditions

Simon, Michael; Schmidt, Eberhard; Kincses, Wilhelm E.; Fritzsche, Martin; Bruns, Andreas; Aufmuth, Claus; Bogdan, Martin; Rosenstiel, Wolfgang; Schrauf, Michael

doi:10.1016/j.clinph.2010.10.044

Cited by 228 publications

(170 citation statements)

References 44 publications

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“…Lal and Craig [4] thought that ECG was an effective physiological signal to evaluate driver fatigue, and they found a significant and large decrease in heart rate in the driving process. Recently, an algorithm for the identification of alpha spindles was described by Simon [5]. He thought EEG alpha spindle parameters increased both fatigue detection sensitivity and specificity as compared to EEG alpha-band power.…”

Section: Introductionmentioning

confidence: 99%

A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors

Wang

Jiang

2017

PROMET

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Section: Introductionmentioning

confidence: 99%

A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors

Wang

Jiang

2017

PROMET

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“…Since driving is a visual task, this can be explained by a decreased processing of visual stimuli due to increasing task-related fatigue which is in line with Simon et al (2011). In contrast, this effect was not observed for alpha band power, making this measure less sensitive to vigilance fluctuations.…”

Section: Time-on-taskmentioning

confidence: 59%

EEG Alpha Spindles as Indicators for Prolonged Brake Reaction Time During Auditory Secondary Tasks in a Real Road Driving Study

Schrauf¹,

Sonnleitner²,

Simon³

et al. 2011

PsycEXTRA Dataset

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Driver distraction accounts for a substantial number of traffic accidents. Therefore, the impact of auditory secondary tasks on driving performance was examined. In addition to performance measures, i.e. reaction time on emergency brakings of a leading vehicle, mental driver states were described by electroencephalographic (EEG: alpha spindles, alpha band power) as well as cardiac activity (ECG: heart rate variability). Results show that brake reaction time (RT) increased with time-on-task during all conditions (p<.001), and was significantly higher while performing the secondary task (p<.001). Physiological measures showed similar effects. Alpha spindle rate, alpha band power as well as heart rate variability (HRV) increased with time-on-task and were significantly different during the secondary task, indicating inhibited visual information processing and reduced concentration ability. This study shows that reduced driving performance measured by means of prolonged brake reactions during increased cognitive load elicited by auditory secondary tasks is indicated by EEG measures as well as cardiac activity, enabling the direct quantification of driver distraction in experiments during real road driving.

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“…ABP was estimated in the same manner as MSP. The alpha burst detector consists of fixed rules and is not an outcome of machine learning (Simon et al, 2011). The central part of this method is the search for such EEG activity which has maximum power in the -band and which has a spectral bandwidth small enough to be a burst activity.…”

Section: Methodsmentioning

confidence: 99%

“…Intrusions of short alpha and theta bursts into beta activity (15-30 Hz) in active subjects under sleepy condition have initially been reported by Torsvall & Åkerstedt (1987). This concept has been extended to quantitatively assess the alpha burst percentage (ABP) and was applied to the EEG of drivers on the real road (Simon et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Driver Sleepiness Assessed by Electroencephalography - Different Methods Applied to One Single Data Set

Gölz

Sommer

Krajewski

2015

Proceedings of the 8th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design: Dri

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Summary: An overview of several methods of electroencephalography (EEG) analysis in order to assess driver sleepiness is presented. All methods were applied to one single data set obtained from overnight driving simulations in our lab. 10 young adults (age 22.4 ± 4.1 years) participated and drove on rural roads; time on task was 7 x 40 min and time since sleep ranged between 16 and 22 hours. Results show large inter-individual variability of all variables and moderate correlation coefficients to one subjective and one objective independent variable of driver drowsiness. Only one method, the detection of microsleep-like EEG patterns, provides a variable with strong increases immediately before sleepiness related crashes. It is concluded that EEG analysis should attach more importance to shortterm patterns and should renounce the analysis of spectral power in four bands.

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EEG alpha spindle measures as indicators of driver fatigue under real traffic conditions

Cited by 228 publications

References 44 publications

A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors

A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors

EEG Alpha Spindles as Indicators for Prolonged Brake Reaction Time During Auditory Secondary Tasks in a Real Road Driving Study

Driver Sleepiness Assessed by Electroencephalography - Different Methods Applied to One Single Data Set

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