Prediction of microsleeps using EEG inter-channel relationships
A microsleep is a brief and involuntary sleep-related loss of consciousness of up to 15 s during an active and attention-demanding task. Such episodes of unresponsiveness are of particularly high importance in people who perform high-risk and monotonous activities requiring extended attention and unimpaired visuomotor performance, such as car and truck drivers, train drivers, pilots, and air-traffic controllers, where microsleeps can, and do, result in catastrophic accidents and fatalities. Microsleep-related accidents can potentially be avoided and thereby lives saved, if microsleeps are noninvasively and accurately predicted. The aim of this study was to explore various inter-channel relationships in the electroencephalogram (EEG) for detection/prediction of microsleeps. In addition to feature-level and decision-level data fusion techniques, ensemble classification techniques were investigated to improve microsleep detection/prediction accuracies.
- Record URL:
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Supplemental Notes:
- PhD thesis
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Authors:
- Buriro, A B
- Publication Date: 2019
Language
- English
Media Info
- Pagination: 113p
Subject/Index Terms
- TRT Terms: Accuracy; Attention; Crash causes; Driver performance; Fatigue (Physiological condition); Sleep; Traffic surveillance
- Uncontrolled Terms: Safe systems (road users)
- Geographic Terms: New Zealand
- ATRI Terms: Accuracy; Attention; Crash cause; Detection; Driver performance; Human fatigue; Sleep patterns
- Subject Areas: Safety and Human Factors;
Filing Info
- Accession Number: 01708491
- Record Type: Publication
- Source Agency: ARRB
- Files: ITRD, ATRI
- Created Date: Jun 25 2019 9:37AM