DOIONLINE 
DOIONLINE Publish In |
International Journal of Soft Computing And Artificial Intelligence (IJSCAI)-IJSCAI |
 Journal Home Volume Issue |
||||||||
Issue |
Volume-2,Issue-1 ( May, 2014 ) | |||||||||
Paper Title |
Multimodal System To Predict Epileptic Seizures Using Machine Learning Technique | |||||||||
Author Name |
A.S. Muthanantha Murugavel, S. Ramakrishnan, B.M.Dhamodharaan, K.Deepak Manavalan | |||||||||
Affilition |
Department of Information Technology, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamilnadu, India | |||||||||
Pages |
67-72 | |||||||||
Abstract |
Abstract— In this paper we proposed a method to an automatic prediction of epilepsy using Multimodal signal. Major aim is to develop a new wireless sensor based system for detecting and monitoring epileptic patients in a non-clinical environment. In order to achieve this, a mechanism will be developed for capturing multi-modal data such as electroencephalogram (EEG), electro dermal activity (EDA), accelerometry (ACM) and heart beat from epileptic patients using EEG cap and wrist-worn biosensor. The captured multi-modal data from sensors will be sent to smart phone through wireless transmission for processing Support Vector Machine (SVM) will be developed and used as classifier The proposed system will sense the aura of pre-ictal stage in advance and takes the necessary safety measures such as alarm, sending SMS along with location information using GPS to emergency medical service, relative and doctor automatically, in order to prevent Sudden Unexpected Death in Epilepsy (SUDEP). | |||||||||
| View Paper | ||||||||||
