Gamma frequency range based EEG analysis for epilepsy detection

dc.contributor.author Padmasai, Y.
dc.contributor.author Rao, K. Subba
dc.contributor.author Rao, C. Raghavendra
dc.contributor.author Jayalakshmi, S. Sita
dc.date.accessioned 2022-03-27T06:00:09Z
dc.date.available 2022-03-27T06:00:09Z
dc.date.issued 2010-01-01
dc.description.abstract A significant portion of the population (0.5%-0.8%) suffers from epilepsy. This study is an effort to predict seizures in epileptic patients. The electroencephalogram (EEG) is one of the most widely used in the bioinformatics field due to its rich information about human tasks. The authors in their previous work demonstrated the use of wavelet transforms in epilepsy detection and its performance. This paper attempts hybridisation of wavelet transforms and fast Fourier transforms (FFT) by transforming wavelet coefficient into spectral components through FFT. The derived data pertaining to frequency band (30-100) Hz which has been considered for classification of the subject as either epileptic or normal. The variations in the amplitude for epileptic subjects significantly depart from the normal in the gamma band. © 2010 Inderscience Enterprises Ltd.
dc.identifier.citation International Journal of Medical Engineering and Informatics. v.2(1)
dc.identifier.issn 17550653
dc.identifier.uri 10.1504/IJMEI.2010.029801
dc.identifier.uri http://www.inderscience.com/link.php?id=29801
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9068
dc.subject Discrete wavelet transform
dc.subject DWT
dc.subject EEG
dc.subject Electroencephalogram
dc.subject Epilepsy
dc.subject Fast fourier transforms
dc.subject FFT
dc.title Gamma frequency range based EEG analysis for epilepsy detection
dc.type Journal. Article
dspace.entity.type
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