Channel selection and feature enhancement for improved epileptic seizure onset detector

Marwa Qaraqe, Muhammad Ismail, Qammer Abbasi, Erchin Serpedin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming Healthcare Through Innovations in Mobile and Wireless Technologies", MOBIHEALTH 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages258-262
Number of pages5
ISBN (Electronic)9781631900143
DOIs
Publication statusPublished - 20 Jan 2015
Externally publishedYes
Event4th International Conference on Wireless Mobile Communication and Healthcare, MOBIHEALTH 2014 - Athens, Greece
Duration: 3 Nov 20145 Nov 2014

Publication series

NameProceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming Healthcare Through Innovations in Mobile and Wireless Technologies", MOBIHEALTH 2014

Conference

Conference4th International Conference on Wireless Mobile Communication and Healthcare, MOBIHEALTH 2014
Country/TerritoryGreece
CityAthens
Period3/11/145/11/14

Keywords

  • EEG
  • Epilepsy
  • Seizure onset

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