Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

Journal: Bio-medical materials and engineering
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure detection is a time-consuming process and may lead to human error; therefore, recently, a number of automated seizure detection frameworks were proposed to replace these traditional methods. Feature extraction and classification are two important steps in these procedures. Feature extraction focuses on finding the informative features that could be used for classification and correct decision-making. Therefore, proposing effective feature extraction techniques for seizure detection is of great significance.

Authors

  • Abeg Kumar Jaiswal
    Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, India. abegiitdhanbad@gmail.com.
  • Haider Banka
    Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, India.