Statistical model for describing heart rate variability in normal rhythm and atrial fibrillation
Электронный научный архив УРФУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
| Заглавие |
Statistical model for describing heart rate variability in normal rhythm and atrial fibrillation
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| Автор |
Markov, N.
Kotov, I. Ushenin, K. Bozhko, Y. |
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| Тематика |
ATRIAL FIBRILLATION
HEART RATE VARIABILITY MACHINE LEARNING STATISTICAL MODEL CARDIOLOGY COMPUTATIONAL COMPLEXITY DISEASES ELECTROCARDIOGRAMS HEART NEAREST NEIGHBOR SEARCH NORMAL DISTRIBUTION ATRIAL FIBRILLATION CARDIAC ARRHYTHMIA CHAOTICS HEART RATE VARIABILITY HUMAN POPULATION MACHINE-LEARNING NORMAL SINUS RHYTHM PROPERTY STATISTIC MODELING VARIABILITY INDEX MACHINE LEARNING |
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| Описание |
Heart rate variability (HRV) indices describe properties of interbeat intervals in electrocardiogram (ECG). Usually HRV is measured exclusively in normal sinus rhythm (NSR) excluding any form of paroxysmal rhythm. Atrial fibrillation (AF) is the most widespread cardiac arrhythmia in human population. Usually such abnormal rhythm is not analyzed and assumed to be chaotic and unpredictable. Nonetheless, ranges of HRV indices differ between patients with AF, yet physiological characteristics which influence them are poorly understood. In this study, we propose a statistical model that describes relationship between HRV indices in NSR and AF. The model is based on Mahalanobis distance, the k-Nearest neighbour approach and multivariate normal distribution framework. Verification of the method was performed using 10 min intervals of NSR and AF that were extracted from long-term Holter ECGs. For validation we used Bhattacharyya distance and Kolmogorov-Smirnov 2-sample test in a k-fold procedure. The model is able to predict at least 7 HRV indices with high precision. © 2022 IEEE.
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| Дата |
2024-04-08T11:07:09Z
2024-04-08T11:07:09Z 2022 |
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| Тип |
Conference paper
Conference object (info:eu-repo/semantics/conferenceObject) info:eu-repo/semantics/submittedVersion |
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| Идентификатор |
Markov, N, Kotov, I, Ushenin, K & Bozhko, Y 2022, Statistical model for describing heart rate variability in normal rhythm and atrial fibrillation. в Proceedings - 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2022. Proceedings - 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2022, Institute of Electrical and Electronics Engineers Inc., стр. 130-133. https://doi.org/10.1109/CSGB56354.2022.9865298
Markov, N., Kotov, I., Ushenin, K., & Bozhko, Y. (2022). Statistical model for describing heart rate variability in normal rhythm and atrial fibrillation. в Proceedings - 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2022 (стр. 130-133). (Proceedings - 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSGB56354.2022.9865298 978-166545288-5 Final All Open Access; Green Open Access https://arxiv.org/pdf/2207.08165 https://arxiv.org/pdf/2207.08165 http://elar.urfu.ru/handle/10995/131415 10.1109/CSGB56354.2022.9865298 85138464136 |
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| Язык |
en
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| Права |
Open access (info:eu-repo/semantics/openAccess)
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| Формат |
application/pdf
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| Издатель |
Institute of Electrical and Electronics Engineers Inc.
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| Источник |
2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB)
Proceedings - 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2022 |
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