High Accuracy Epileptic Seizure Detection System Based on Wearable Devices Using Support Vector Machine Classifier

Abstract

This paper aims to develop an efficient and reliable epileptic seizure detection system based on different wearable devices using support vector machine (SVM) classification. The proposed seizure detection system achieves Seizure detection results show that our algorithm achieving an average sensitivity of 100% and an average accuracy 97% with proposed different combining methods for the signals of wearable devices.