Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments

Evangelos Kafantaris; Ian Piper; Tsz-Yan Milly Lo; Javier Escudero

doi:10.1109/EMBC.2019.8856554

Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments

Evangelos Kafantaris, Ian Piper, Tsz-Yan Milly Lo, Javier Escudero

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2019)
Publisher	Institute of Electrical and Electronics Engineers
Pages	2269-2272
Number of pages	4
ISBN (Electronic)	978-1-5386-1311-5
DOIs	https://doi.org/10.1109/EMBC.2019.8856554
Publication status	Published - Jul 2019
Event	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society - City Cube Berlin, Berlin, Germany Duration: 23 Jul 2019 → 27 Jul 2019

Conference

Conference	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated title	EMBC'19
Country/Territory	Germany
City	Berlin
Period	23/07/19 → 27/07/19

Access to Document

10.1109/EMBC.2019.8856554

https://ieeexplore.ieee.org/document/8856554

Paediatric Brain Monitoring with Information Technology (KidsBrainIT): Using Information Technology (IT) Innovations to improve childhood brain trauma
Escudero Rodriguez, J.
MRC
1/08/17 → 31/08/20
Project: Research

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Kafantaris, E., Piper, I., Lo, T.-Y. M., & Escudero, J. (2019). Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments. In Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2019) (pp. 2269-2272). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2019.8856554

@inproceedings{4035e29fea4d4873a11d22645b1354eb,

title = "Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments",

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.",

author = "Evangelos Kafantaris and Ian Piper and Lo, {Tsz-Yan Milly} and Javier Escudero",

note = "Acceptance date set to exclude from REF OA Policy; 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society , EMBC'19 ; Conference date: 23-07-2019 Through 27-07-2019",

year = "2019",

month = jul,

doi = "10.1109/EMBC.2019.8856554",

language = "English",

pages = "2269--2272",

booktitle = "Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2019)",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

}

Kafantaris, E, Piper, I , Lo, T-YM & Escudero, J 2019, Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments. in Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2019). Institute of Electrical and Electronics Engineers, pp. 2269-2272, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society , Berlin, Germany, 23/07/19. https://doi.org/10.1109/EMBC.2019.8856554

Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments. / Kafantaris, Evangelos; Piper, Ian ; Lo, Tsz-Yan Milly et al.
Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2019). Institute of Electrical and Electronics Engineers, 2019. p. 2269-2272.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments

AU - Kafantaris, Evangelos

AU - Piper, Ian

AU - Lo, Tsz-Yan Milly

AU - Escudero, Javier

N1 - Acceptance date set to exclude from REF OA Policy

PY - 2019/7

Y1 - 2019/7

N2 - 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.

AB - 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.

U2 - 10.1109/EMBC.2019.8856554

DO - 10.1109/EMBC.2019.8856554

M3 - Conference contribution

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EP - 2272

BT - Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2019)

PB - Institute of Electrical and Electronics Engineers

T2 - 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 23 July 2019 through 27 July 2019

ER -

Application of Dispersion Entropy to Healthy and Pathological Heartbeat ECG Segments

Abstract

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Paediatric Brain Monitoring with Information Technology (KidsBrainIT): Using Information Technology (IT) Innovations to improve childhood brain trauma

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