Cui, J, Huang, Z, Wu, J et al. (3 more authors) (2022) Model-based Assessment of cardiopulmonary autonomic regulation in paced deep breathing. Methods, 204. pp. 312-318. ISSN 1046-2023
Abstract
Autonomic dysfunction can lead to many physical and psychological diseases. The assessment of autonomic regulation plays an important role in the prevention, diagnosis, and treatment of these diseases. A physiopathological mathematical model for cardiopulmonary autonomic regulation, namely Respiratory-Autonomic-Sinus (RSA) regulation Model, is proposed in this study. A series of differential equations are used to simulate the whole process of RSA phenomenon. Based on this model, with respiration signal and ECG signal simultaneously acquired in paced deep breathing scenario, we manage to obtain the cardiopulmonary autonomic regulation parameters (CARP), including the sensitivity of respiratory-sympathetic nerves and respiratory-parasympathetic nerves, the time delay of sympathetic, the sensitivity of norepinephrine and acetylcholine receptor, as well as cardiac remodeling factor by optimization algorithm. An experimental study has been conducted in healthy subjects, along with subjects with hypertension and coronary heart disease. CARP obtained in the experiment have shown their clinical significance.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Elsevier Inc. All rights reserved. This is an author produced version of an article, published in Methods. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Autonomic nerve; Respiratory sinus arrhythmia; Cardiopulmonary differential equation model; Cardiac measurement |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Apr 2022 11:31 |
Last Modified: | 18 Apr 2023 00:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ymeth.2022.04.008 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186010 |