Pathologies affect the performance of ECG signals compression
Abstract The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-89817-w |
| _version_ | 1818990744748163072 |
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| author | Andrea Nemcova Radovan Smisek Martin Vitek Marie Novakova |
| author_facet | Andrea Nemcova Radovan Smisek Martin Vitek Marie Novakova |
| author_sort | Andrea Nemcova |
| collection | DOAJ |
| description | Abstract The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published. |
| first_indexed | 2024-12-20T19:59:15Z |
| format | Article |
| id | doaj.art-f0a57693d6f0444689a72521c86311ab |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-20T19:59:15Z |
| publishDate | 2021-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f0a57693d6f0444689a72521c86311ab2022-12-21T19:28:06ZengNature PortfolioScientific Reports2045-23222021-05-011111910.1038/s41598-021-89817-wPathologies affect the performance of ECG signals compressionAndrea Nemcova0Radovan Smisek1Martin Vitek2Marie Novakova3Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of TechnologyDepartment of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of TechnologyDepartment of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of TechnologyDepartment of Physiology, Faculty of Medicine, Masaryk UniversityAbstract The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.https://doi.org/10.1038/s41598-021-89817-w |
| spellingShingle | Andrea Nemcova Radovan Smisek Martin Vitek Marie Novakova Pathologies affect the performance of ECG signals compression Scientific Reports |
| title | Pathologies affect the performance of ECG signals compression |
| title_full | Pathologies affect the performance of ECG signals compression |
| title_fullStr | Pathologies affect the performance of ECG signals compression |
| title_full_unstemmed | Pathologies affect the performance of ECG signals compression |
| title_short | Pathologies affect the performance of ECG signals compression |
| title_sort | pathologies affect the performance of ecg signals compression |
| url | https://doi.org/10.1038/s41598-021-89817-w |
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