Detection of Epilepsy Using MFCC-Based Feature and XGBoost

Abstract

This paper develops a MFCC-based feature for detection of epilepsy, since inspired by some methods in speech signal processing, and tests the reliability of the feature through experiments. Our experimental results show that the method using MFCC-based feature and XGBoost has a high accuracy of 99.5% in epilepsy detection, reaching the level of the state-of-the-art method. This work has some inspiration for exploring better epilepsy detection methods.