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Design and Optimization of ECG Modeling for Generating Different Cardiac Dysrhythmias

2021Journal article Open access
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dc.contributor.authorAwal, Md. Abdul
dc.contributor.authorMostafa, Sheikh Shanawaz
dc.contributor.authorAhmad, Mohiuddin
dc.contributor.authorAlahe, Mohammad Ashik
dc.contributor.authorRashid, Mohd Abdur
dc.contributor.authorKouzani, Abbas Z.
dc.contributor.authorMahmud, M. A. Parvez
dc.date.accessioned2024-04-24T13:34:44Z
dc.date.available2024-04-24T13:34:44Z
dc.date.issued2021
dc.description.abstractThe electrocardiogram (ECG) has significant clinical importance for analyzing most cardio vascular 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, fit ting 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 coeffi cients (>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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAwal, M..A.; Mostafa, S.S.; Ahmad, M.; Alahe, M.A.; Rashid, M.A.; Kouzani, A.Z.; Mahmud, M.A.P. Design and Optimization of ECG Modeling for Generating Different Cardiac Dysrhythmias. Sensors 2021, 21, 1638. https://doi.org/10.3390/ s21051638pt_PT
dc.identifier.doi10.3390/s21051638pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/5646
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationLaboratory of Robotics and Engineering Systems
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectECG modelingpt_PT
dc.subjectECG generatorpt_PT
dc.subjectGaussian functionpt_PT
dc.subjectOptimizationpt_PT
dc.subjectData compressionpt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleDesign and Optimization of ECG Modeling for Generating Different Cardiac Dysrhythmiaspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleLaboratory of Robotics and Engineering Systems
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50009%2F2020/PT
oaire.citation.issue5pt_PT
oaire.citation.startPage1638pt_PT
oaire.citation.titleSensorspt_PT
oaire.citation.volume21pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameAWAL
person.familyNameMostafa
person.familyNameAhmad
person.familyNameKouzani
person.familyNameMahmud
person.givenNameMD. ABDUL
person.givenNameSheikh Shanawaz
person.givenNameMohiuddin
person.givenNameAbbas Z.
person.givenNameM A Parvez
person.identifier34497
person.identifier2800364
person.identifier56983
person.identifier2359052
person.identifier.ciencia-idEE14-BEB3-F82B
person.identifier.orcid0000-0003-3028-4932
person.identifier.orcid0000-0002-7677-0971
person.identifier.orcid0000-0001-9123-0618
person.identifier.orcid0000-0002-6292-1214
person.identifier.orcid0000-0002-1905-6800
person.identifier.ridN-9228-2015
person.identifier.scopus-author-id55489640900
person.identifier.scopus-author-id57202296170
person.identifier.scopus-author-id57162659800
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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