Analysis of Blood Pressure Morphology as a Fingerprint of Cardiovascular Health using A Machine Learning Based Approach
DOI:
https://doi.org/10.33414/ajea.1127.2022Keywords:
Cardiovascular health, automatic learning, pulse wave velocityAbstract
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
Section
Proceedings - Signal and Image Processing
