Epileptic seizure detection using DWT based fuzzy approximate entropy and support vector machine

• Published in: Neurocomputing (Amsterdam) Vol. 133; pp. 271 - 279
• Main Authors: Kumar, Yatindra, Dewal, M.L., Anand, R.S.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 10.06.2014; Elsevier
• Subjects: Applied sciences; Approximation; Biological and medical sciences; Classification; Computer science; control theory; systems; Data processing. List processing. Character string processing; Discrete wavelet transform (DWT); Electrodiagnosis. Electric activity recording; Electroencephalogram (EEG); Electroencephalography; Entropy; Exact sciences and technology; Fuzzy; Fuzzy approximate entropy (fApEn); Fuzzy logic; Fuzzy set theory; Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy; Investigative techniques, diagnostic techniques (general aspects); Medical sciences; Memory organisation. Data processing; Nervous system; Nervous system (semeiology, syndromes); Neurology; Software; Support vector machines; Support vector machines (SVMs); Discrete wavelet transform (DWT); Support vector machines (SVMs); Electroencephalogram (EEG); Fuzzy approximate entropy (fApEn); Chaos; Subband decomposition; Epilepsy; Electroencephalography; Entropy; Discrete wavelet transforms; Modeling; Complex variable method; Radial basis function; Fuzzy logic; Wavelet transformation; Vector support machine; Mental disorder

Epilepsy is a common neurological condition which affects the central nerve system that causes people to have a seizure and can be assessed by electroencephalogram (EEG). A wavelet based fuzzy approximate entropy (fApEn) method is presented for the classification of electroencephalogram (EEG) signal...