Circular insights for rhythmic health: A Bayesian approach with stochastic diffusion for characterizing human physiological rhythms with applications to arrhythmia detection.
Accurate detection of arrhythmic patterns in physiological signals-particularly electrocardiogram (ECG)-is vital for early diagnosis and intervention. Traditional amplitude-based models often fail to capture disruptions in the underlying phase dynamics. In this study, we propose a novel Bayesian fra...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Public Library of Science (PLoS)
2025-01-01
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| Col·lecció: | PLoS ONE |
| Accés en línia: | https://doi.org/10.1371/journal.pone.0324741 |
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