DECOMPOSITION OF EEG SIGNAL USING WAVELET TRANSFORM

Khushbu Vyas

Abstract: Epileptic seizures are manifestations of epilepsy. The detection of epileptic form discharges in the EEG is an important component in the diagnosis of epilepsy. Around 1% of the total population of the world is suffering from this problem. The present works aim at the classification of the EEG pattern we need to decompose it into different level.Decomposition is done using Daubechies wavelet order 8 (db8) transform which is very popular and efficient technique. Once the decomposition is done into different levels, we get subbands of signal and called as brain waves (delta, theta, alpha, beta, and gamma). Important features such as minimum, maximum, mean, standard deviation, median has been calculated. These features will be used for the classification.

Keywords: Epilepsy, (Electroencephalography)EEG, Brain waves, Wavelet transform, Feature extraction

DOI: https://doi.org/10.15623/ijret.2018.0701007