Epileptic Seizure Detection Using Deep Learning Based Long Short-Term Memory Networks and Time-Frequency Analysis: a Comparative Investigation in Machine Learning Paradigm

Abstract

under 10-fold cross-validation technique. Further, when the top 30 most relevant features selected by different feature selection techniques are used for classification, the proposed approach achieves similar performance followed by BPANN which reports 99.4% classification accuracy when combined with the Relief F feature selection technique.