MCA Based Epilepsy EEG Classification Using Time Frequency Domain Features.
Annu Int Conf IEEE Eng Med Biol Soc
; 2018: 3398-3401, 2018 Jul.
Article
em En
| MEDLINE
| ID: mdl-30441117
ABSTRACT
In this work, we proposed a morphological component analysis (MCA) based method for epilepsy classification using the explicit dictionary of independent redundant transforms to decomposes the electroencephalogram (EEG) by considering it's morphology. Output components of MCA are represented into analytical form by using Hilbert transform. Then features, parameter's ratio of bandwidth square, mean square frequency and fractional contributions to dominant frequency were extracted to discriminate epilepsy EEG by support vector machine (SVM). These features have shown classification results comparable to previous works.
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Base de dados:
MEDLINE
Assunto principal:
Epilepsia
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article