Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments

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

Abstract

Entropy quantification algorithms are a prominent tool for the quantification of irregularity in biological signal segments towards the characterization of the physiological state of individuals. This paper investigates the potential of Dispersion Entropy (DisEn) as a non-linear method to quantify the uncertainty of ECG signal segments for different types of heartbeats and the stratification of healthy heartbeats for the potential detection of developing pathologies in individuals. Our results indicate that the DisEn algorithm produces distributions with significant differences for the considered types of heartbeats, with higher DisEn values being more prominent in pathological heartbeats and normal heartbeats preceding them. This suggests that, with further research, DisEn algorithms can be integrated with heartbeat detection and classification algorithms for the improvement of medical prognosis through ECG signal processing.
Original languageEnglish
Title of host publicationProceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2019)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2269-2272
Number of pages4
ISBN (Electronic)978-1-5386-1311-5
DOIs
Publication statusPublished - Jul 2019
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society - City Cube Berlin, Berlin, Germany
Duration: 23 Jul 201927 Jul 2019

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated titleEMBC'19
CountryGermany
CityBerlin
Period23/07/1927/07/19

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