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Design and optimization of ECG modeling for generating different cardiac dysrhythmias

Awal, MA, Mostafa, SS, Ahmad, M, Alahe, MA, Rashid, MA, Kouzani, A and Mahmud, MAP 2021, Design and optimization of ECG modeling for generating different cardiac dysrhythmias, Sensors, vol. 21, no. 5, pp. 1-26, doi: 10.3390/s21051638.

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Title Design and optimization of ECG modeling for generating different cardiac dysrhythmias
Author(s) Awal, MA
Mostafa, SS
Ahmad, M
Alahe, MA
Rashid, MA
Kouzani, AORCID iD for Kouzani, A orcid.org/0000-0002-6292-1214
Mahmud, MAPORCID iD for Mahmud, MAP orcid.org/0000-0002-1905-6800
Journal name Sensors
Volume number 21
Issue number 5
Start page 1
End page 26
Total pages 26
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2021-02-26
ISSN 1424-8220
Keyword(s) ECG modeling
ECG generator
Gaussian function
optimization
data compression
Summary The electrocardiogram (ECG) has significant clinical importance for analyzing most cardiovascular diseases. ECGs beat morphologies, beat durations, and amplitudes vary from subject to subject and diseases to diseases. Therefore, ECG morphology-based modeling has long-standing research interests. This work aims to develop a simplified ECG model based on a minimum number of parameters that could correctly represent ECG morphology in different cardiac dysrhythmias. A simple mathematical model based on the sum of two Gaussian functions is proposed. However, fitting more than one Gaussian function in a deterministic way has accuracy and localization problems. To solve these fitting problems, two hybrid optimization methods have been developed to select the optimal ECG model parameters. The first method is the combination of an approximation and global search technique (ApproxiGlo), and the second method is the combination of an approximation and multi-start search technique (ApproxiMul). The proposed model and optimization methods have been applied to real ECGs in different cardiac dysrhythmias, and the effectiveness of the model performance was measured in time, frequency, and the time-frequency domain. The model fit different types of ECG beats representing different cardiac dysrhythmias with high correlation coefficients (>0.98). Compared to the nonlinear fitting method, ApproxiGlo and ApproxiMul are 3.32 and 7.88 times better in terms of root mean square error (RMSE), respectively. Regarding optimization, the ApproxiMul performs better than the ApproxiGlo method in many metrics. Different uses of this model are possible, such as a syntactic ECG generator using a graphical user interface has been developed and tested. In addition, the model can be used as a lossy compression with a variable compression rate. A compression ratio of 20:1 can be achieved with 1 kHz sampling frequency and 75 beats per minute. These optimization methods can be used in different engineering fields where the sum of Gaussians is used.
Language eng
DOI 10.3390/s21051638
Indigenous content off
Field of Research 0301 Analytical Chemistry
0805 Distributed Computing
0906 Electrical and Electronic Engineering
0502 Environmental Science and Management
0602 Ecology
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2021, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30148535

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.