Automatic recognition of vigilance state by using a wavelet-based artificial neural network

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dc.contributor.authorSubasi, A
dc.contributor.authorKiymik, MK
dc.contributor.authorAkin, M
dc.contributor.authorErogul, O
dc.date.accessioned2024-04-24T16:01:55Z
dc.date.available2024-04-24T16:01:55Z
dc.date.issued2005
dc.departmentDicle Üniversitesien_US
dc.description.abstractIn this study, 5-s long sequences of full-spectrum electroencephalogram (EEG) recordings were used for classifying alert versus drowsy states in an arbitrary subject. EEG signals were obtained from 30 healthy subjects and the results were classified using a wavelet-based neural network. The wavelet-based neural network model, employing the multilayer perceptron (MLP), was used for the classification of EEG signals. A multilayer perceptron neural network (MLPNN) trained with the Levenberg-Marquardt algorithm was used to discriminate the alertness level of the subject. In order to determine the MLPNN inputs, spectral analysis of EEG signals was performed using the discrete wavelet transform (DWT) technique. The MLPNN was trained, cross-validated, and tested with training, cross-validation, and testing sets, respectively. The correct classification rate was 93.3% alert, 96.6% drowsy, and 90% sleep. The classification results showed that the MLPNN trained with the Levenberg-Marquardt algorithm was effective for discriminating the vigilance state of the subject.en_US
dc.identifier.doi10.1007/s00521-004-0441-0
dc.identifier.endpage55en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-17444384508
dc.identifier.scopusqualityQ1
dc.identifier.startpage45en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-004-0441-0
dc.identifier.urihttps://hdl.handle.net/11468/14494
dc.identifier.volume14en_US
dc.identifier.wosWOS:000228978000006
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAlerten_US
dc.subjectDrowsyen_US
dc.subjectSleepen_US
dc.subjectEegen_US
dc.subjectDiscrete Wavelet Transform (Dwt)en_US
dc.subjectMultilayer Perceptron Neural Network (Mlpnn)en_US
dc.subjectLevenberg-Marquardt Algorithmen_US
dc.titleAutomatic recognition of vigilance state by using a wavelet-based artificial neural networken_US
dc.titleAutomatic recognition of vigilance state by using a wavelet-based artificial neural network
dc.typeArticleen_US

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