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The estimation of cardiac power output using multiple physiological signals. / CUHK electronic theses & dissertations collection

1. An explicit mathematical description of PEP in terms of DBP was proposed, which in the first time quantitatively clarified the ventricular and arterial effects on PEP timing. / 2. A nonlinear pressure-volume relationship which reflected the natural arterial wall properties was introduced into the asymmetric T-tube arterial model, which effectively and quantitatively described the effect of pulsatile BP on arterial parameters, e.g., compliance, PTT etc. / 3. A mathematical relationship between PAT and BP was firstly proposed as a result of the heart-arterial interaction, which simulated a significantly strong and negative relationship between PAT and SBP and between PAT and MBP but a much weaker negative relationship between PAT and DBP during exercise. The hypothesis was supported by the experiment data. To our knowledge, it is the first study describing the quantitative relation of PAT and BP by both model-based study and experimental data. / 4. A novel wearable measurable CO parameter, PTRR, was proposed and it successfully showed a significantly high and positive correlation with CO during exercise both in model simulation and in the experiments. / 5. Linear prediction models using PAT to estimate MBP and using PTRR to estimate CO were proposed and evaluated in two exercise experiments conducted on 84 subjects with different ages and cardiovascular diseases. Results showed the proposed method could achieve the accuracy required for medical diagnosis. / 6. Taken the findings in 3, 4 and 5 together, this study in the first time provided both the theoretical basis and experimental verifications of developing a wearable and direct measurement technique of CPO in dynamic exercise using multiple physiological signals measured on body surface. / Cardiac power output (CPO) is defmed as the product of mean arterial blood pressure (MBP) and cardiac output (CO), and CPO measured during peak dynamic exercise (i.e. peak CPO) has been shown as a powerful predictor of death for heart failure patients. However, so far there has been no existing device which directly measures CPO, and CPO is acquired from simultaneous measurement of MBP and CO. Further, simultaneous MBP and CO measurement during dynamic exercise is a challenge for current BP and CO methods. Therefore, there is an urgent need to develop new devices which are fully wearable and unobtrusive for monitoring of CPO during dynamic exercise. Since the core problem in most wearable devices is how to estimate the target cardiovascular parameter, e.g. CPO in this study, through physiological signals measured from body surface, this thesis focus on developing a direct measurement technique of CPO in dynamic exercise using multiple physiological signals measured on body surface, specifically, electrocardiogram (ECG) and photoplehtysmogram (PPG). / Finally, based on the theoretical and experimental verifications, linear prediction models were proposed to estimate MBP from PAT and estimate CO from PTRR. The results showed that PAT can estimate MBP with a standard deviation of 7.42 mmHg, indicating PAT model has the potential to achieve the accuracy required by AMMI standard (mean error within +/- 5 mmHg and SD less than 8 mmHg). The results also showed that PTRR can estimate CO with a percent error of 22.57%, showing an accuracy which was considered as clinically acceptable (percent error less than 30%). / Heart failure is the end stage of many cardiovascular diseases, such as hypertension, coronary heart disease, diabetes mellitus, etc. Around 5.8 million people in the United States have heart failure and about 670,000 people are diagnosed with it each year. In 2010, heart failure will cost the United States $30.2 billion, and the cost of healthcare services is a major component of this total. With the resultant burden on health care resources it is imperative that heart failure patients with different risk stages are identified, ideally with objective indicators of cardiac dysfunction, in order that appropriate and effective treatment can be instituted. / In order to verify the theoretical findings, two experiments were carried out. One was incremental supine bicycle exercise conducted on 19 young healthy subjects and the other was incremental to maximum supine bicycle exercise conducted on 65 subjects, including heart failure patients, cardiovascular patients and healthy elderly. PAT showed significantly high and negative correlation with SBP and MBP, but lower correlation with DBP. PTRR showed significantly high and positive correlation with CO. / In this thesis, a model based study is conducted to address the above problem. Firstly, we deduced the mathematical expression of PEP as a function of DBP by introducing the arbitrary heart rate into the exponential mathematical description of a pressure-source model. Secondly, an asymmetric T-tube model was modified by introducing a nonlinear pressure-volume relationship where PTT was expressed as a dependent variant of BP. Thirdly, we proposed the mathematical equation between PAT and BP by coupling the modified ventricular and arterial models. Then, the relationships between PAT with systolic blood pressure (SBP), MBP and DBP were simulated under changing heart contractility, preload, heart rate, peripheral resistance, arterial stiffness and a mimic exercise condition. The simulation results indicated significantly high and negative correlations between PAT and SBP and between PAT and MBP whereas the correlation between DBP and PAT was low. / Next, we developed a novel CO index, namely pulse time reflection ratio (PTRR), expressed in terms of MBP and mean aortic reflection coefficient (Gamma(0)), from the modified asymmetric T-tube model. PTRR was further expressed in terms of PAT and inflection point area (IPA), a surrogate of Gamma(0) from the shape feature of PPG. The simulation results suggested significantly and positive relationship between PTRR and CO and between IPA and Gamma(0) during dynamic exercise. / Recently, a wearable measurable parameter, pulse arrival time or PAT, has been developed for BP measurement. PAT is the time delay from the R peak of ECG to the systolic foot of PPG. PAT consists of two timing components, the pre-ejection period (PEP) of the heart and pulse transit time (PTT). PTT is related to BP by an arterial elastic model and thus can be used to estimate beat-to-beat BP. However, PTT is difficult to be measured through a wearable device, and thus PAT is usually used as a surrogate of PTT for BP estimation, under the assumption of a constant PEP. However, PEP is not a constant but changing with physiological conditions, which may alter the PAT-BP relationship. Thus, it is important to clarify the PAT-BP relationship and address the feasibility of MBP estimation using PAT during dynamic exercise. / To summarize, the original contributions of this thesis are: / Wang, Ling. / Adviser: Y.T. Zhang. / Source: Dissertation Abstracts International, Volume: 73-03, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_344888
Date January 2010
ContributorsWang, Ling, Chinese University of Hong Kong Graduate School. Division of Electronic Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, theses
Formatelectronic resource, microform, microfiche, 1 online resource (xiv, 142 leaves : ill.)
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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