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  • In this paper, the equal frequency discretization (EFD) based probability density approach was proposed to be used in the diagnosis of epilepsy from electroencephalogram (EEG) signals. For this aim, EEG signals were decomposed by using the discrete wavelet discretization (DWT) method into subbands, the coefficients in each subband were discretized to several intervals by EFD method, and the probability density of each subband of each EEG segment was computed according to the number of coefficients in discrete intervals. Then, two probability density functions were defined by means of the curve fitting over the probability densities of the sets of both healthy subjects and epilepsy patients. EEG signals were classified by applying the mean square error (MSE) criterion to these functions. The result of the classification was evaluated by using the ROC analysis, which indicated 82.50% success in the diagnosis of epilepsy. As a result, the EFD based probability density approach may be considered as an alt
  • In this paper, the equal frequency discretization (EFD) based probability density approach was proposed to be used in the diagnosis of epilepsy from electroencephalogram (EEG) signals. For this aim, EEG signals were decomposed by using the discrete wavelet discretization (DWT) method into subbands, the coefficients in each subband were discretized to several intervals by EFD method, and the probability density of each subband of each EEG segment was computed according to the number of coefficients in discrete intervals. Then, two probability density functions were defined by means of the curve fitting over the probability densities of the sets of both healthy subjects and epilepsy patients. EEG signals were classified by applying the mean square error (MSE) criterion to these functions. The result of the classification was evaluated by using the ROC analysis, which indicated 82.50% success in the diagnosis of epilepsy. As a result, the EFD based probability density approach may be considered as an alt (en)
Title
  • Epilepsy diagnosis using probability density functions of EEG signals
  • Epilepsy diagnosis using probability density functions of EEG signals (en)
skos:prefLabel
  • Epilepsy diagnosis using probability density functions of EEG signals
  • Epilepsy diagnosis using probability density functions of EEG signals (en)
skos:notation
  • RIV/00216305:26220/11:PU93434!RIV12-MSM-26220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S, Z(MSM0021630513)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 197839
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/11:PU93434
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • curve fitting, EEG signals, epilepsy, equal frequency discretization, mean square error, probability density, wavelet transform (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [06C68F4A05F1]
http://linked.open...v/mistoKonaniAkce
  • Instanbul
http://linked.open...i/riv/mistoVydani
  • Istanbul
http://linked.open...i/riv/nazevZdroje
  • Proceedings of INISTA 2011
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Provazník, Ivo
  • Hekim, Mahmut
  • Orhan, Umut
  • Ozer, Mahmut
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • IEEE
https://schema.org/isbn
  • 978-1-61284-919-5
http://localhost/t...ganizacniJednotka
  • 26220
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