Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals
Abstract Nowadays, Electrocardiogram (ECG) signals can be measured using wearable devices, such as smart watches. Most wearable devices provide only a few details; however, they have the advantage of recording data in real time. In this study, 12-lead ECG signals were generated from lead I and their...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-52216-y |
| _version_ | 1797276625723719680 |
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| author | Gi-Won Yoon Segyeong Joo |
| author_facet | Gi-Won Yoon Segyeong Joo |
| author_sort | Gi-Won Yoon |
| collection | DOAJ |
| description | Abstract Nowadays, Electrocardiogram (ECG) signals can be measured using wearable devices, such as smart watches. Most wearable devices provide only a few details; however, they have the advantage of recording data in real time. In this study, 12-lead ECG signals were generated from lead I and their feasibility was tested to obtain more details. The 12-lead ECG signals were generated using a U-net-based generative adversarial network (GAN) that was trained on ECG data obtained from the Asan Medical Center. Subsequently, unseen PTB-XL PhysioNet data were used to produce real 12-lead ECG signals for classification. The generated and real 12-lead ECG signals were then compared using a ResNet classification model; and the normal, atrial fibrillation (A-fib), left bundle branch block (LBBB), right bundle branch block (RBBB), left ventricular hypertrophy (LVH), and right ventricular hypertrophy (RVH) were classified. The mean precision, recall, and f1-score for the real 12-lead ECG signals are 0.70, 0.72, and 0.70, and that for the generated 12-lead ECG signals are 0.82, 0.80, and 0.81, respectively. In our study, according to the result generated 12-lead ECG signals performed better than real 12-lead ECG. |
| first_indexed | 2024-03-07T15:30:55Z |
| format | Article |
| id | doaj.art-9fd682e1f10a41c29cdaa913689157c9 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-07T15:30:55Z |
| publishDate | 2024-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-9fd682e1f10a41c29cdaa913689157c92024-03-05T16:25:29ZengNature PortfolioScientific Reports2045-23222024-01-0114111010.1038/s41598-024-52216-yClassification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signalsGi-Won Yoon0Segyeong Joo1Department of Biomedical Engineering, Asan Medical Center, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of MedicineDepartment of Biomedical Engineering, Asan Medical Center, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of MedicineAbstract Nowadays, Electrocardiogram (ECG) signals can be measured using wearable devices, such as smart watches. Most wearable devices provide only a few details; however, they have the advantage of recording data in real time. In this study, 12-lead ECG signals were generated from lead I and their feasibility was tested to obtain more details. The 12-lead ECG signals were generated using a U-net-based generative adversarial network (GAN) that was trained on ECG data obtained from the Asan Medical Center. Subsequently, unseen PTB-XL PhysioNet data were used to produce real 12-lead ECG signals for classification. The generated and real 12-lead ECG signals were then compared using a ResNet classification model; and the normal, atrial fibrillation (A-fib), left bundle branch block (LBBB), right bundle branch block (RBBB), left ventricular hypertrophy (LVH), and right ventricular hypertrophy (RVH) were classified. The mean precision, recall, and f1-score for the real 12-lead ECG signals are 0.70, 0.72, and 0.70, and that for the generated 12-lead ECG signals are 0.82, 0.80, and 0.81, respectively. In our study, according to the result generated 12-lead ECG signals performed better than real 12-lead ECG.https://doi.org/10.1038/s41598-024-52216-y |
| spellingShingle | Gi-Won Yoon Segyeong Joo Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals Scientific Reports |
| title | Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals |
| title_full | Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals |
| title_fullStr | Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals |
| title_full_unstemmed | Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals |
| title_short | Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals |
| title_sort | classification feasibility test on multi lead electrocardiography signals generated from single lead electrocardiography signals |
| url | https://doi.org/10.1038/s41598-024-52216-y |
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