Machine Learning Algorithms for Epilepsy Detection Based on Published EEG Databases: A Systematic Review

Epilepsy is the only neurological condition for which electroencephalography (EEG) primary diagnostic and important prognostic clinical tool. However, manual inspection of EEG signals a time-consuming procedure neurologists. Thus, intense research has been made on creating machine learning methodologies automated epilepsy detection. Also, many or medical facilities have published databases epileptic to accommodate this effort. The vast number studies concerning detection with makes systematic review necessary. It presents detailed evaluation signal processing classification employed different provides valuable insights future work. 190 were included in according PRISMA guidelines, acquired from literature search PubMed, Scopus, ScienceDirect IEEE Xplore 1st May 2021. Studies examined based Signal Transformation technique, methodology database evaluation. Along other findings, increasing tendency employ Convolutional Neural Networks that use combination Time-Frequency decomposition images noticed.