Automatic drowsiness detection using electroencephalogram signal

Drowsiness refers to the state of being sleepy or the state of minimal concentration. It is characterised by a decrease in a person's memory capacity and brain information processing speed. These conditions cause hazards in the real-time working environment such as driving, monitoring power gen...

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Veröffentlicht in:	Electronics letters Jg. 56; H. 25; S. 1383 - 1386
Hauptverfasser:	Dutta, A, Kour, S, Taran, S
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 10.12.2020
Schlagworte:	automatic drowsiness detection system band‐limited modes clustering variational mode decomposition CVMD optimum allocation sampling analyses nonhomogenous EEG signals drowsiness detection performance electroencephalogram signal electroencephalogram‐based automatic drowsiness detection method electroencephalography hazards least squares approximations medical signal processing minimal concentration neural nets neurophysiology nonstationary behaviour oscillatory mode characteristics patient health person power generation real‐time working environment signal classification Special Issue: Current Trends in Cognitive Science and Brain Computing Research and Applications support vector machines electroencephalography nonstationary behaviour least squares approximations support vector machines electroencephalogram signal drowsiness detection performance patient health real-time working environment CVMD optimum allocation sampling analyses nonhomogenous EEG signals signal classification medical signal processing hazards person minimal concentration electroencephalogram-based automatic drowsiness detection method power generation clustering variational mode decomposition neurophysiology automatic drowsiness detection system band-limited modes neural nets oscillatory mode characteristics
ISSN:	0013-5194, 1350-911X, 1350-911X
Online-Zugang:	Volltext
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