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.


  • English

Media Info

  • Pagination: 113p

Subject/Index Terms

Filing Info

  • Accession Number: 01708491
  • Record Type: Publication
  • Source Agency: ARRB
  • Files: ITRD, ATRI
  • Created Date: Jun 25 2019 9:37AM