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 t...Show MoreMetadata
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.
Published in: 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
Date of Conference: 13-15 October 2018
Date Added to IEEE Xplore: 03 February 2019
ISBN Information: