Detection and Classification of Epileptic Seizures using Wavelet feature extraction and Adaptive Neuro-Fuzzy Inference System
نویسندگان
چکیده
Epilepsy, a neurological disorder in which patients suffer from recurring seizures, affects approximately 1% of the world population. In this work, an attempt has been made to enhance the diagnostic importance of EEG using Adaptive neuro fuzzy inference system (ANFIS) and Wavelet transform coefficients. For this study, EEG for 20 normal and 30 seizure subjects under standard recording procedure is used. A method based on wavelet transform and ANFIS is used to detect the epileptic seizures. Further, BPN algorithm is used to study and compare the datasets. Average specificity of 99% and sensitivity of 97% are obtained. Results show that the ANFIS is able to detect seizure. It appears that this method of detection makes it possible as a real-time detector, which will improve the clinical service of Electroencephalographic recording.
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