Arterial pulse wave modeling and analysis for vascular-age studies: a review from VascAgeNet

Author:

Alastruey Jordi1ORCID,Charlton Peter H.2ORCID,Bikia Vasiliki34ORCID,Paliakaite Birute5ORCID,Hametner Bernhard6ORCID,Bruno Rosa Maria7ORCID,Mulder Marijn P.8ORCID,Vennin Samuel1ORCID,Piskin Senol9ORCID,Khir Ashraf W.10,Guala Andrea1112ORCID,Mayer Christopher C.6ORCID,Mynard Jonathan131415ORCID,Hughes Alun D.16ORCID,Segers Patrick17ORCID,Westerhof Berend E.1819ORCID

Affiliation:

1. Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom

2. Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

3. Division of Vascular Surgery, School of Medicine, Stanford University, Stanford, California, United States

4. Laboratory of Hemodynamics and Cardiovascular Technology, Institute of Bioengineering, Swiss Federal Institute of Technology, Lausanne, Switzerland

5. Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania

6. AIT Austrian Institute of Technology, Center for Health and Bioresources, Medical Signal Analysis, Vienna, Austria

7. INSERM, U970, Paris Cardiovascular Research Center, Université de Paris, Hopital Europeen Georges Pompidou–APHP, Paris, France

8. Cardiovascular and Respiratory Physiology, TechMed Centre, University of Twente, Enschede, The Netherlands

9. Department of Mechanical Engineering, Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, Turkey

10. Department of Engineering, Durham University, Durham, United Kingdom

11. Vall d’Hebron Institut de Recerca, Barcelona, Spain

12. CIBER-CV, Instituto de Salud Carlos III, Madrid, Spain

13. Heart Research, Murdoch Children’s Research Institute, Parkville, Victoria, Australia

14. Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia

15. Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria, Australia

16. MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom

17. Institute for Biomedical Engineering and Technology, Ghent University, Ghent, Belgium

18. Department of Pulmonary Medicine, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

19. Department of Neonatology, Radboud University Medical Center, Radboud Institute for Health Sciences, Amalia Children’s Hospital, Nijmegen, The Netherlands

Abstract

Arterial pulse waves (PWs) such as blood pressure and photoplethysmogram (PPG) signals contain a wealth of information on the cardiovascular (CV) system that can be exploited to assess vascular age and identify individuals at elevated CV risk. We review the possibilities, limitations, complementarity, and differences of reduced-order, biophysical models of arterial PW propagation, as well as theoretical and empirical methods for analyzing PW signals and extracting clinically relevant information for vascular age assessment. We provide detailed mathematical derivations of these models and theoretical methods, showing how they are related to each other. Finally, we outline directions for future research to realize the potential of modeling and analysis of PW signals for accurate assessment of vascular age in both the clinic and in daily life.

Funder

EU Horizon 2020

Kaunas University of Technology

European Commission | European Research Executive Agency

British Heart Foundation

European Cooperation in Science and Technology

Istinye University

la Caixa’ Foundation

National Institute for Health and Care Research

Publisher

American Physiological Society

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine,Physiology

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Aging models make waves: predicting vascular aging in virtual patients;American Journal of Physiology-Heart and Circulatory Physiology;2023-12-01

2. Noninvasive hemodynamic indices of vascular aging: an in silico assessment;American Journal of Physiology-Heart and Circulatory Physiology;2023-12-01

3. Mechanistic insights on age-related changes in heart-aorta-brain hemodynamic coupling using a pulse wave model of the entire circulatory system;American Journal of Physiology-Heart and Circulatory Physiology;2023-11-01

4. Interpretable and accurate curve‐fitting method for arterial pulse wave modeling and decomposition;International Journal for Numerical Methods in Biomedical Engineering;2023-09-23

5. Exploring Arterial Wave Frequency Features for Vascular Age Assessment through Supervised Learning with Risk Factor Insights;Applied Sciences;2023-09-22

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