A new e-health cloud-based system for cardiovascular risk assessment
Sudden cardiac death (SCD) is one of the leading causes of death worldwide. Many individuals have no cardiovascular symptoms before the SCD event. As a result, the ability to identify the risk before such an event is extremely limited. Timely and accurate prediction of SCD using new electronic techn...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-12-01
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| Series: | Frontiers in Electronics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/felec.2023.1315132/full |
| _version_ | 1827576547702210560 |
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| author | G. Tatsis G. Baldoumas V. Christofilakis P. Kostarakis P. A. Varotsos N. V. Sarlis E. S. Skordas A. Bechlioulis L. K. Michalis K. K. Naka |
| author_facet | G. Tatsis G. Baldoumas V. Christofilakis P. Kostarakis P. A. Varotsos N. V. Sarlis E. S. Skordas A. Bechlioulis L. K. Michalis K. K. Naka |
| author_sort | G. Tatsis |
| collection | DOAJ |
| description | Sudden cardiac death (SCD) is one of the leading causes of death worldwide. Many individuals have no cardiovascular symptoms before the SCD event. As a result, the ability to identify the risk before such an event is extremely limited. Timely and accurate prediction of SCD using new electronic technologies is greatly needed. In this work, a new innovative e-health cloud-based system is presented that allows a stratification of SCD risk based on the method of natural time entropy variability analysis. This innovative, non-invasive system can be used easily in any setting. The e-health cloud-based system was evaluated using data from a total of 203 individuals, patients with chronic heart failure (CHF) who are at high risk of SCD and age-matched healthy controls. Statistical analysis was performed in two-time windows of different duration; the first-time window had a duration of 20 min, while the second was 10 min. Employing modern methods of machine learning, classifiers for the discrimination of CHF patients from the healthy controls were obtained for the first as well as the second (half-time) window. The results indicated a very good separation between the two groups, even from samples taken in a 10-min time window. Larger studies are needed to further validate this novel e-health cloud-based system before its use in everyday clinical practice. |
| first_indexed | 2024-03-08T21:13:04Z |
| format | Article |
| id | doaj.art-1f236536fd8b45d8a47a4501fefada00 |
| institution | Directory Open Access Journal |
| issn | 2673-5857 |
| language | English |
| last_indexed | 2024-03-08T21:13:04Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Electronics |
| spelling | doaj.art-1f236536fd8b45d8a47a4501fefada002023-12-22T04:31:08ZengFrontiers Media S.A.Frontiers in Electronics2673-58572023-12-01410.3389/felec.2023.13151321315132A new e-health cloud-based system for cardiovascular risk assessmentG. Tatsis0G. Baldoumas1V. Christofilakis2P. Kostarakis3P. A. Varotsos4N. V. Sarlis5E. S. Skordas6A. Bechlioulis7L. K. Michalis8K. K. Naka9Electronics-Telecommunications and Applications Laboratory, Physics Department, University of Ioannina, Ioannina, GreeceElectronics-Telecommunications and Applications Laboratory, Physics Department, University of Ioannina, Ioannina, GreeceElectronics-Telecommunications and Applications Laboratory, Physics Department, University of Ioannina, Ioannina, GreeceElectronics-Telecommunications and Applications Laboratory, Physics Department, University of Ioannina, Ioannina, GreeceSection of Condensed Matter Physics, Department of Physics, National and Kapodistrian University of Athens, Athens, GreeceSection of Condensed Matter Physics, Department of Physics, National and Kapodistrian University of Athens, Athens, GreeceSection of Condensed Matter Physics, Department of Physics, National and Kapodistrian University of Athens, Athens, Greece2nd Department of Cardiology and Michaelidion Cardiac Center, Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece2nd Department of Cardiology and Michaelidion Cardiac Center, Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece2nd Department of Cardiology and Michaelidion Cardiac Center, Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, GreeceSudden cardiac death (SCD) is one of the leading causes of death worldwide. Many individuals have no cardiovascular symptoms before the SCD event. As a result, the ability to identify the risk before such an event is extremely limited. Timely and accurate prediction of SCD using new electronic technologies is greatly needed. In this work, a new innovative e-health cloud-based system is presented that allows a stratification of SCD risk based on the method of natural time entropy variability analysis. This innovative, non-invasive system can be used easily in any setting. The e-health cloud-based system was evaluated using data from a total of 203 individuals, patients with chronic heart failure (CHF) who are at high risk of SCD and age-matched healthy controls. Statistical analysis was performed in two-time windows of different duration; the first-time window had a duration of 20 min, while the second was 10 min. Employing modern methods of machine learning, classifiers for the discrimination of CHF patients from the healthy controls were obtained for the first as well as the second (half-time) window. The results indicated a very good separation between the two groups, even from samples taken in a 10-min time window. Larger studies are needed to further validate this novel e-health cloud-based system before its use in everyday clinical practice.https://www.frontiersin.org/articles/10.3389/felec.2023.1315132/fullnatural time analysiselectrocardiographyphotoplethysmographychronic heart failuresudden cardiac death |
| spellingShingle | G. Tatsis G. Baldoumas V. Christofilakis P. Kostarakis P. A. Varotsos N. V. Sarlis E. S. Skordas A. Bechlioulis L. K. Michalis K. K. Naka A new e-health cloud-based system for cardiovascular risk assessment Frontiers in Electronics natural time analysis electrocardiography photoplethysmography chronic heart failure sudden cardiac death |
| title | A new e-health cloud-based system for cardiovascular risk assessment |
| title_full | A new e-health cloud-based system for cardiovascular risk assessment |
| title_fullStr | A new e-health cloud-based system for cardiovascular risk assessment |
| title_full_unstemmed | A new e-health cloud-based system for cardiovascular risk assessment |
| title_short | A new e-health cloud-based system for cardiovascular risk assessment |
| title_sort | new e health cloud based system for cardiovascular risk assessment |
| topic | natural time analysis electrocardiography photoplethysmography chronic heart failure sudden cardiac death |
| url | https://www.frontiersin.org/articles/10.3389/felec.2023.1315132/full |
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