Analysis of Blood Pressure Morphology as a Fingerprint of Cardiovascular Health using A Machine Learning Based Approach

Authors

  • Eugenia Ipar Grupo de Investigación y Desarrollo en Bioingeniería, Facultad Regional Buenos Aires, Universidad Tecnológica Nacional - Argentina
  • Leandro J. Cymberknop Director
  • Ricardo L. Armentano Codirector

DOI:

https://doi.org/10.33414/ajea.1127.2022

Keywords:

Cardiovascular health, automatic learning, pulse wave velocity

Abstract

Results obtained from the estimation of several key parameters, such as pulse wave velocity, related to cardiovascular health using a one-dimensional (1-D) model as part of the machine learning models training, are presented, as well as the verification of these predictions using real signals obtained from a measurement protocol.

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Published

2022-10-03

How to Cite

Ipar, E., Cymberknop, L. J., & Armentano, R. L. (2022). Analysis of Blood Pressure Morphology as a Fingerprint of Cardiovascular Health using A Machine Learning Based Approach. AJEA (Proceedings of UTN Academic Conferences and Events), (15). https://doi.org/10.33414/ajea.1127.2022

Conference Proceedings Volume

No. 15 (2022): VI Conference on Exchange and Dissemination of Research Results of Doctoral Students in Engineering

Section

Signal and Image Processing