Exploring Deep Learning Approaches for Epileptic Seizure Classification

A seizure is an uncontrollable electrical disruption in the brain that modifies movement, sensations, behaviour, and consciousness. Individuals with epilepsy are likely to suffer recurrent seizures. Seizures based on EEG data have been classified using deep learning and machine learning techniques to aid in epilepsy identification. In this work, LSTM, Bi-Directional LSTM, Stacked LSTM, and GRU are checked to obtain the most suitable classification model. The model is then utilized to identify the class of the testing data. Also, the accuracy, precision, and sensitivity of the model are determined in Two-Class Classification, Three-Class Classification and Five-Class Classification for obtaining reliable results.