Estimating pulse wave velocity from the radial pressure wave using machine learning algorithms

One of the European gold standard measurement of vascular ageing, a risk factor for cardiovascular disease, is the carotid-femoral pulse wave velocity (cfPWV), which requires an experienced operator to measure pulse waves at two sites. In this work, two machine learning pipelines were proposed to es...

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Veröffentlicht in:	PloS one Jg. 16; H. 6; S. e0245026
Hauptverfasser:	Jin, Weiwei, Chowienczyk, Philip, Alastruey, Jordi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 28.06.2021 Public Library of Science (PLoS)
Schlagworte:	Accuracy Adult Aged Aging Algorithms Analysis Biology and Life Sciences Biomedical engineering Blood Pressure Cardiovascular diseases Cardiovascular Diseases - diagnostic imaging Cardiovascular Diseases - prevention & control Carotid Arteries - diagnostic imaging Carotid Arteries - physiology Carotid-Femoral Pulse Wave Velocity - methods Computer and Information Sciences Diagnosis Disease Elastic waves Engineering and Technology Evaluation Feature extraction Female Femoral Artery - diagnostic imaging Femoral Artery - physiology Gaussian process Health risks Heart Rate Humans Learning algorithms Libraries Machine Learning Male Medical tests Medicine and Health Sciences Middle Aged Mortality Neural networks Physical Sciences Pipelines Population studies Pressure Principal components analysis Pulse Wave Analysis - methods Radial Artery - diagnostic imaging Radial Artery - physiology Random noise Recurrent neural networks Research and Analysis Methods Risk analysis Risk Factors Vascular Stiffness - physiology Velocity Wave analysis Wave velocity Waveforms United Kingdom United Kingdom > UK
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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