eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2017-12-21 10 4 2061 2069 10.13005/bpj/1328 18132 article Nitendra Kumar 1 Khursheed Alam 1 Abul Hasan Siddiqi 1 Department of Applied Sciences, school of Engineering and Technology, Sharda University, Greater Noida, Delhi (NCR) India,- 201306. One of the most challenging research areas in the field of biomedical signal is feature extraction and classification of electroencephalogram (EEG) signal for normal and epileptic patients. Epileptic seizures are manifestations of epilepsy and epileptic seizures are disclosures of epilepsy. This paper illustrates the use of wavelet transform (WT) used for feature extraction of EEG signals and the classifiers used are Artificial Neural Network (ANN) and Support Vector Machine (SVM). For feature extraction the EEG signal is decomposed using Daubechies wavelet. Performances of classifiers are based on the parameters such as Accuracy, Sensitivity and Specificity. https://biomedpharmajournal.org/vol10no4/wavelet-transform-for-classification-of-eeg-signal-using-svm-and-ann/ Artificial Neural Network(ANN) EEG Signal Support Vector Machine (SVM) Wavelet Transform