Automatic recognition of congestive heart failure signs in heart rate variability data-Reference-Cited by-同舟云学术

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

Published:2022-06-07 Issue: Volume: Page:
ISSN:
Container-title:2022 11th Mediterranean Conference on Embedded Computing (MECO)
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Author:

Pulavskyi A.A.¹,Krivenko S.S.¹,Krivenko S.A.²,Linskiy I.V.³,Posokhov M.F.³,Kryvenko L.S.⁴

Affiliation:

1. Scientific Company KOLIBRI LLC,Karkiv,Ukraine

2. Kharkiv National University of radioelectronics,Kharkiv,Ukraine

3. Institute of Neurology, Psychiatry and Narcology of the National Academy of Medical Sciences of Ukraine,Kharkiv,Ukraine

4. Kharkiv National Medical University,Kharkiv,Ukraine

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9797068/9797069/09797210.pdf?arnumber=9797210

Reference19 articles.

1. Accuracy improvement of noninvasive determination of glucose concentration in human blood;krivenko;2013 12th International Conference on the Experience of Designing and Application of CAD Systems in Microelectronics (CADSM) CADSM,0

2. A convolutional neural network approach to detect congestive heart failure

3. Classifying cardiac biosignals using ordinal pattern statistics and symbolic dynamics

4. Quantifying heart rate dynamics using different approaches of symbolic dynamics

5. A Fast Method of Visually Lossless Compression of Dental Images

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