Feature Selection for the Detection of Epilepsy by using EEG Physiological Signal

Volume 4 Issue 2 June - August 2017

Research Paper

Feature Selection for the Detection of Epilepsy by using EEG Physiological Signal

Manisha Chandani*, S. Arun Kumar**

*PG Student, Department of Electronics and Telecommunication Engineering, Bhilai Institute of Technology, Durg, India.

** Associate Professor, Department of Electronics and Telecommunication Engineering, Bhilai Institute of Technology, Durg, India.

Chandani, M., and Kumar, A., (2017). Feature Selection for the Detection of Epilepsy by using EEG Physiological Signal. i-manager’s Journal on Pattern Recognition, 4(2), 17-21. https://doi.org/10.26634/jpr.4.2.13727

Abstract

The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. Epilepsy is one of the most common neurological diseases and the most common neurological chronic disease in childhood. Electroencephalography (EEG) still remains one in all the foremost helpful and effective tools in understanding and treatment of brain disorder. EEG signal once broken down into the frequency subbands, offers many applied mathematics features in every band. A number of these features, that will be used for detection of brain disorder are explored in this paper. The objective of this study is the analysis of epileptic seizure by using these features more suitable in real time, and for a reliable automatic epileptic seizure detection system to enhance the patient's care and the quality of life.