Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals

• Published in: International journal of neural systems Vol. 22; no. 2; p. 1250002
• Main Authors: Acharya, U Rajendra, Sree, S Vinitha, Alvin, Ang Peng Chuan, Yanti, Ratna, Suri, Jasjit S
• Format: Journal Article
• Language: English
• Published: Singapore 01.04.2012
• Subjects: Analysis of Variance; Brain Waves - physiology; Electroencephalography; Entropy; Epilepsy - classification; Epilepsy - diagnosis; Epilepsy - physiopathology; Humans; Neural Networks (Computer); Nonlinear Dynamics; Signal Processing, Computer-Assisted; Support Vector Machine

Epilepsy, a neurological disorder, is characterized by the recurrence of seizures. Electroencephalogram (EEG) signals, which are used to detect the presence of seizures, are non-linear and dynamic in nature. Visual inspection of the EEG signals for detection of normal, interictal, and ictal activiti...