Combined matching pursuit and wigner-ville distribution analysis for the discrimination of ictal heart rate variability

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents a novel method for the discrimination of ictal heart rate variability (HRV). Traditionally, the analysis of the non-linear and non-stationary electrocardiogram (ECG) signal is limited to the time-domain or frequency-domain. This severely limits the quality of features that can be extracted from the ECG signal. In this work, HRV extracted from ECG is analyzed by combining the Matching-Pursuit (MP) and Wigner-Ville Distribution (WVD) algorithms in order to obtain a high quality time-frequency distribution of the HRV signal and to effectively extract meaningful HRV features representative of seizure and non-seizure states. The proposed method is tested on clinical patients and the results demonstrate effective discrimination between ictal HRV features and non-ictal HRV features.

Original languageEnglish
Title of host publication2016 24th European Signal Processing Conference, EUSIPCO 2016
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages2045-2049
Number of pages5
Volume2016-November
ISBN (Electronic)9780992862657
DOIs
Publication statusPublished - 28 Nov 2016
Event24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary
Duration: 28 Aug 20162 Sep 2016

Other

Other24th European Signal Processing Conference, EUSIPCO 2016
CountryHungary
CityBudapest
Period28/8/162/9/16

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ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Qaraqe, M., Muhammad, M. I., & Serpedin, E. (2016). Combined matching pursuit and wigner-ville distribution analysis for the discrimination of ictal heart rate variability. In 2016 24th European Signal Processing Conference, EUSIPCO 2016 (Vol. 2016-November, pp. 2045-2049). [7760608] European Signal Processing Conference, EUSIPCO. https://doi.org/10.1109/EUSIPCO.2016.7760608