Channel Selection and Feature Enhancement for Improved Epileptic Seizure Onset Detector Conference Paper uri icon

abstract

  • © 2014 ICST. This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography. The proposed architecture exploits the benefits of both channel selection and feature enhancement to improve the detector performance. The novel architecture results in higher energy difference between the pre-seizure and seizure states and hence performs better in terms of detection sensitivity and false alarm rate compared to benchmark detectors available in the literature. In detail, the proposed architecture achieves a 7% increase in sensitivity and a reduction of 9 false alarms per hour compared to the benchmark detector.

published proceedings

  • 2014 4th International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH)

author list (cited authors)

  • Qaraqe, M., Ismail, M., Abbasi, Q., & Serpedin, E

citation count

  • 2

complete list of authors

  • Qaraqe, Marwa||Ismail, Muhammad||Abbasi, Qammer||Serpedin, Erchin

editor list (cited editors)

  • Nikita, K. S., Bourbakis, N. G., Lo, B., Fotiadis, D. I., Hao, Y., & Kiourti, A.

publication date

  • November 2014