Epileptic EEG detection using neural networks and post-classification

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dc.contributor.authorPatnaik, L.M.
dc.contributor.authorManyam, O.K.
dc.date.accessioned2026-02-05T09:36:54Z
dc.date.issued2008
dc.description.abstractElectroencephalogram (EEG) has established itself as an important means of identifying and analyzing epileptic seizure activity in humans. In most cases, identification of the epileptic EEG signal is done manually by skilled professionals, who are small in number. In this paper, we try to automate the detection process. We use wavelet transform for feature extraction and obtain statistical parameters from the decomposed wavelet co-efficients. A feed-forward backpropagating artificial neural network (ANN) is used for the classification. We use genetic algorithm for choosing the training set and also implement a post-classification stage using harmonic weights to increase the accuracy. Average specificity of 99.19%, sensitivity of 91.29% and selectivity of 91.14% are obtained. © 2008 Elsevier Ireland Ltd. All rights reserved.
dc.identifier.citationComputer Methods and Programs in Biomedicine, 2008, 91, 2, pp. 100-109
dc.identifier.issn1692607
dc.identifier.urihttps://doi.org/10.1016/j.cmpb.2008.02.005
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/27721
dc.subjectDiscrete wavelet transforms
dc.subjectFeature extraction
dc.subjectGenetic algorithms
dc.subjectNeural networks
dc.subjectResilient backpropagation
dc.subjectSkilled professionals
dc.subjectElectroencephalography
dc.subjectaccuracy
dc.subjectarticle
dc.subjectartificial neural network
dc.subjectautomation
dc.subjectdata extraction
dc.subjectdisease classification
dc.subjectelectroencephalogram
dc.subjectepilepsy
dc.subjectgenetic algorithm
dc.subjectsensitivity and specificity
dc.subjectstatistical parameters
dc.subjectAlgorithms
dc.subjectDiagnosis, Computer-Assisted
dc.subjectEpilepsy
dc.subjectHumans
dc.subjectNeural Networks (Computer)
dc.subjectPattern Recognition, Automated
dc.subjectReproducibility of Results
dc.subjectSensitivity and Specificity
dc.titleEpileptic EEG detection using neural networks and post-classification

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