A Study on EEG Signals for Epileptic Seizure Detection using Machine Learning Classifiers

The advancement in Artificial Intelligence (AI) and Machine Learning (ML) techniques helps to employ the clinical practice applications for Epilepsy seizure detection. The present research reviews advance techniques in health care and Epilepsy disease prediction to prevent further interventions. The consequences of epileptic seizures are avoided through advanced prediction of the disease and is remained to be the unsolved issue. The major problems that occurred in the existing machine learning models are likely due to an inadequate amount of data usage that obtained poor results. The advanced ML-based technologies have proven to be potentially useful for paradigm shift delivery for accurate and early prediction of epilepsy disease. The present research work provides a comprehensive review for all the state-of-the-art ML techniques applied for seizure detection at an early stage by using Electroencephalograph (EEG) signals. The present research work identifies the challenges and research gaps that occurred in existing researches, and also recommendations for future implementations.