BALLISTOCARDIOGRAPHY: MATHEMATICAL MODELING, ANALYSIS, AND APPLICATION TO CARDIOVASCULAR HEALTH MONITORING

Abstract

The main goal of this dissertation is to improve the early detection and management of cardiovascular (CV) disease by developing novel ultra-convenient CV health and risk predictor monitoring techniques based on a physiological signal called ballistocardiogram (BCG). BCG is the recording of heart-induced body movements. It has great potential to enable ultra-convenient CV health monitoring due to its close association with cardiac functions and its amenity for convenient measurement (i.e., measurement devices such as weighing scales and wearables). Nonetheless, the shortage of physical understanding of the BCG is a serious challenge that has hampered its effective use in CV health and risk assessment. The scope of this dissertation can be explained under three themes: (i) physics-based modeling of BCG, (ii) BCG recording, and (iii) challenges in wearable BCG-based cuffless blood pressure monitoring. In the first part of the dissertation, a closed-form physics-based model is developed to estimate BCG from a single blood pressure waveform. The feasibility of this model in the estimation of CV risk predictors is studied. This model is inspired by our team’s prior work hypothesizing that the main mechanism for the genesis of the head-to-foot BCG is the pressure gradients in the ascending and descending aorta (the major artery in the body). In addition, a systematic BCG feature selection approach is introduced leveraging the developed closed-form BCG model. This model-based approach is superior to previous ad-hoc feature selection techniques in that it incorporates physiological knowledge of the arterial system and unlike ad-hoc approaches which are data specific its findings can be generalized to different independent datasets. BCG waveforms recorded with different sensors and devices have morphological differences. Therefore, the next part of this work is dedicated to the study of different BCG recording devices and the construction of a BCG measurement apparatus that enables the recording of true BCG (as estimated in the mathematical model). The efficacy of the BCG recording apparatus in measuring BCG is shown in two human and animal experiments. Finally, BCG can enable cuff-less blood pressure (BP) tracking by virtue of two perks. It can easily be instrumented using wearables and it can be used as a proximal timing reference to calculate pulse transit time (PTT) which is the basis of the most common technique for cuff-less BP tracking. However, most wearable BCG-based studies for cuff-less BP monitoring have resorted to only one posture (standing with hands placed on the sides). Therefore, in this work, the effect of posture on wrist BCG-PPG PTT is investigated. This work reveals the posture-induced changes in PTT in-depth for the first time, by invoking and quantifying the effect of possible physical mechanisms responsible for such changes.