Heartbeat classification based on single lead-II ECG using deep learning

Issa, Mohamed F.; Yousry, Ahmed; Tuboly, Gergely; Juhász, Zoltan; AbuEl-Atta, Ahmed H.; Selim, Mazen M.

doi:10.1016/j.heliyon.2023.e17974

Cited by 7 publications

(4 citation statements)

References 22 publications

(28 reference statements)

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“…The usage of single channel ECG in optimizing the physical stress test such as bicycle ergometry [1] . Additionally, single channel ECG results can be interpreted using machine learning models to increase the diagnostic accuracy and used as a novel risk score for future cardiovascular events [10] .…”

Section: Discussionmentioning

confidence: 99%

“…Several kinds of single channel ECG has been used in the clinical trials including CARDO-QVARK , Apple Watch, Kardia, Zio, BioHarness, Bittium Faros and Carnation Ambulatory Monitor [1][2][3][4][5][6][7][8] . Single channel ECG has been used to diagnosis myocardial infarction and monitoring patients with chronic heart disease and heart failure as well as to classify heartbeat [9][10][11] .…”

Section: Introductionmentioning

confidence: 99%

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Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

Marzoog,

Abdullaev,

Suvorov

et al. 2024

Preprint

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Background: Cardiovascular disease (CVD) such as ischemic heart disease impacts the people quality of life and has the highest mortality rate in the globe. This returns to the poor diagnostic and therapeutic strategies including the early prevention methods. Aims: To assess the changes in the single channel electrocardiography (SCECG) in rest and on exercise test in patients with vs without ischemic heart disease confirmed by stress computed tomography myocardial perfusion (CTP) imaging. Objectives: Ischemic heart disease patients frequently have preventable risk factors and causes that lead to the disease appearance. However, the lack of the proper diagnostic and prevention tools remains a global challenge in or era despite the current scientific advances. Material and methods: A cohort, prospective, single center observational study included 38 participants from Moscow. The participants aged ≥ 40 years and given a written consent to participate in the study. The participants subdivided into two groups according to the presence or absence of the myocardial perfusion defect on the CTP with vasodilatation stress-test. Both groups (group 1 with myocardial perfusion defect (n=19), group 2 without myocardial perfusion defect (n=19)) passed general primary consultation by cardiologist, anthropometric measurements, recording 3-minutes single channel electrocardiography (ECG) in rest before and just after exercise test, blood pressure and pulse rate using automatic tonometer, echocardiography, cardio-ankle vascular index, performing ergometry, immediately repeating the single channel ECG, then performing CTP. LASSO regression with nested cross-validation was used to find association between Cardio-Qvark parameters and the existence of the perfusion defect. Statistical processing was carried out using the R programming language v4.2 and Python v.3.10 [^R]. Results: The study results showed that the single channel ECG have significantly higher diagnostic accuracy in compare to bicycle ergometry. The specificity 63.2 % [95 % confidence interval (CI); 0.391 ; 0.833], sensitivity 73.7 % [95 % CI ; 0.533 ; 0.929], and accuracy of the diagnostic method using exhaled breath analysis, area under the curve (AUC) 68.4 % [95 % CI ; 0.527 ; 0.817]. Conclusion: Single channel ECG (Cardio-Qvark) has the potential to improve the diagnostic accuracy of the bicycle ergometry. Other: Further investigations required to uncover the hidden capabilities of Cardio-Qvark in the diagnosis of ischemic heart disease.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

Marzoog,

Abdullaev,

Suvorov

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Single channel ECG results can be interpreted using machine learning models to increase the diagnostic accuracy and reduce the consumed time for interpretation of the results by the physicians. Additionally, the primary data of the single channel ECG (approximately 200 parameter) can be used as a novel risk scoring for future IHD development or death due to [10].…”

Section: Discussionmentioning

confidence: 99%

“…Several kinds of single channel ECG has been used in the clinical trials including CARDO-QVARK , Apple Watch, Kardia, Zio, BioHarness, Bittium Faros and Carnation Ambulatory Monitor [1][2][3][4][5][6][7][8]. Single channel ECG has been used to diagnosis myocardial infarction and monitoring patients with chronic heart disease and heart failure as well as to classify heartbeat [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

CARDIO-QVARK Diagnose Ischemic Myocardiocyte!

Marzoog,

Chomakhidze,

Suvorov

et al. 2024

Preprint

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BackgroundIschemic heart disease (IHD) has the highest mortality rate in the globe. This returns to the poor diagnostic and therapeutic strategies including the early prevention methods.AimsTo assess the changes in the single channel electrocardiography (SCECG) at rest and on exercise test in patients with vs without IHD confirmed by stress computed tomography myocardial perfusion (CTP) imaging with vasodilatation stress-test.ObjectivesIHD frequently have preventable risk factors and causes that lead to the disease appearance. However, the lack of the proper diagnostic and prevention tools remains a global challenge in or era despite the current scientific advances.Material and methodsA single center observational study included 80 participants from Moscow. The participants aged ≥ 40 years and given a written consent to participate in the study. Both groups, G1=31 with vs G2=49 without post stress induced myocardial perfusion defect, passed cardiologist consultation, anthropometric measurements, blood pressure and pulse rate, echocardiography, cardio-ankle vascular index, performing bicycle ergometry, recording 3-minutes SCECG (using CARDO-QVARK) before and just after bicycle ergometry, and then performing CTP. The LASSO regression with nested cross-validation was used to find association between CARDO-QVARK parameters and the existence of the perfusion defect. Statistical processing carried out using the R programming language v4.2, Python v.3.10 [^R], and Statistica 12 programme.ResultsThe CARDO-QVARK parameters analysis have a specificity 75.5 % [95 % confidence interval (CI); 0.628; 0.88], sensitivity 51.6 % [95 % CI; 0.333; 0.695], area under the curve (AUC) 67 % [95 % CI; 0.530; 0.801] in compare to bicycle ergometry AUC; 50.7 % [95 % CI; 0.388; 0.625], specificity 53.1 % [95 % CI; 0.392; 0.673], sensitivity 48.4 % [95 % CI; 0.306; 0.657], based on our study results.ConclusionThe SCECG have no statistically significant higher diagnostic accuracy in compare to bicycle ergometry. However, CARDO-QVARK has the potential to improve the diagnostic accuracy of the bicycle ergometry.OtherFurther investigations required to uncover the hidden capabilities of CARDO-QVARK in the diagnosis of ischemic heart disease.

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DIFDD: Deep intelligence framework for disease detection using patients electrocardiogram signals and X-ray images

Goyal,

Singh

2024

Multimed Tools Appl

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Heartbeat classification based on single lead-II ECG using deep learning

Cited by 7 publications

References 22 publications

Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

CARDIO-QVARK Diagnose Ischemic Myocardiocyte!

DIFDD: Deep intelligence framework for disease detection using patients electrocardiogram signals and X-ray images

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