Detection of Epileptic Seizure Using a Combination of Discrete Wavelet Transform and Power Spectral Density

Epileptic seizure is detected by reading the electroencephalogram (EEG) signals which are obtained from the electrical activities of the brain which are containing information about the brain. Epileptic seizure is known as the abrupt abnormal activity of a bunch of neurons which results in an electric surge in the brain. India is also one of the countries on the globe which is having about 10 million people suffering from a seizure. In this paper, the combination of discrete wavelet transform along with power spectral density is proposed for the classification and feature extraction process to detect epileptic seizures. To achieve high accuracy of seizure detection rate and explore relevant knowledge from the EEG processed dataset, deep learning has been used. The result shows that the detection of epileptic seizures using the proposed method gives an accuracy of 90.1%. This system would be useful for clinical analysis of epileptic seizures, and appropriate action would be taken against epileptic seizures.