Seizure Detection Using Gilbert’s Algorithm

Abstract

Seizure detection for epileptic patients can be done using Support Vector Machines (SVMs). SVMs are a well- established method in classification between seizure and nonseizure points. One of the SVM trainers is Gilbert’s Algorithm. This paper elaborates Gilbert’s Algorithm role in training SVM to succeed in performing seizure detection. FPGA is used to accelerate the SVM training because of its reconfigurability. The reached results are highlighted and discussed as well as the used power and resources.