Automatic recognition of congestive heart failure signs in heart rate variability data

Pulavskyi, A. A.; Krivenko, S. S.; Krivenko, S. A.; Linskiy, I. V.; Posokhov, M. F.; Kryvenko, L. S.

Публікація:
Automatic recognition of congestive heart failure signs in heart rate variability data

dc.contributor.author	Pulavskyi, A. A.
dc.contributor.author	Krivenko, S. S.
dc.contributor.author	Krivenko, S. A.
dc.contributor.author	Linskiy, I. V.
dc.contributor.author	Posokhov, M. F.
dc.contributor.author	Kryvenko, L. S.
dc.date.accessioned	2022-07-18T20:40:22Z
dc.date.available	2022-07-18T20:40:22Z
dc.date.issued	2022
dc.description.abstract	Automatic screening of the population for congestive heart failure (CHF) is a matter of pressing concern due to the severity of the health consequences resulting in disability and death of people. On the one hand, portable devices working with ECG signals become convenient tools for the lay user due to the simplicity. On the other hand, analyzing the specific behavior of the R-peaks sequence (analysis of heart rate variability) in cardiac pathologies allows identifying the patterns inherent in particular heart dysfunction. Such patterns are effectively differentiated using symbolic dynamics methods and the subsequent application of machine learning methods. In this study, a highly specific model was obtained (sensitivity 0.71, specificity 0.96), suitable for automatic screening of CHF. Its operability and performance characteristics have been verified through testing in several publicly available databases.	uk_UA
dc.identifier.citation	A. A. Pulavskyi, S. S. Krivenko, S. A. Krivenko, I. V. Linskiy, M. F. Posokhov and L. S. Kryvenko, "Automatic recognition of congestive heart failure signs in heart rate variability data," 2022 11th Mediterranean Conference on Embedded Computing (MECO), 2022, pp. 01-05, doi: 10.1109/MECO55406.2022.9797210.	uk_UA
dc.identifier.other	DOI: 10.1109/MECO55406.2022.9797210
dc.identifier.uri	https://openarchive.nure.ua/handle/document/20714
dc.language.iso	en	uk_UA
dc.publisher	IEEE	uk_UA
dc.subject	Congestive heart failure	uk_UA
dc.subject	Heart	uk_UA
dc.subject	Sequences	uk_UA
dc.subject	Sensitivity	uk_UA
dc.subject	Telemedicine	uk_UA
dc.subject	Sociology	uk_UA
dc.subject	Databases	uk_UA
dc.title	Automatic recognition of congestive heart failure signs in heart rate variability data	uk_UA
dc.type	Abstract of Thesis	uk_UA
dspace.entity.type	Publication