The reductionist approach has dominated the fields of biology and medicine for nearly a century. Here, we present a systems science approach to the analysis of physiological waveforms in the context of a specific case, cardiovascular physiology. Our goal in this study is to introduce a methodology that allows for novel insight into cardiovascular physiology and to show proof of concept for a new index for the evaluation of the cardiovascular system through pressure wave analysis. This methodology uses a modified version of sparse time-frequency representation (STFR) to extract two dominant frequencies we refer to as intrinsic frequencies (IFs; v 1 and v 2 ). The IFs are the dominant frequencies of the instantaneous frequency of the coupled heart þ aorta system before the closure of the aortic valve and the decoupled aorta after valve closure. In this study, we extract the IFs from a series of aortic pressure waves obtained from both clinical data and a computational model. Our results demonstrate that at the heart rate at which the left ventricular pulsatile workload is minimized the two IFs are equal (v 1 ¼ v 2 ). Extracted IFs from clinical data indicate that at young ages the total frequency variation (Dv ¼ v 1 2 v 2 ) is close to zero and that Dv increases with age or disease (e.g. heart failure and hypertension). While the focus of this paper is the cardiovascular system, this approach can easily be extended to other physiological systems or any biological signal.

Analysis of carotid waveforms using intrinsic frequency methods can be used to document left ventricular ejection fraction with accuracy comparable with that of MRI. The measurements require no training to perform or interpret, no calibration, and can be repeated at the bedside to generate almost continuous analysis of left ventricular ejection fraction without arterial cannulation.

No abstract

No abstract

Over the past two decades, a variety of micropumps have been explored for various applications in microfluidics such as control of pico-and nanoliter flows for drug delivery as well as chemical mixing and analysis. We present the fabrication and preliminary experimental studies of flow performance on the micro impedance pump, a previously unexplored method of pumping fluid on the microscale. The micro impedance pump was constructed of a simple thin-walled tube coupled at either end to glass capillary tubing and actuated electromagnetically. Through the cumulative effects of wave propagation and reflection originating from an excitation located asymmetrically along the length of the elastic tube, a pressure head can be established to drive flow. Flow rates were observed to be reversible and highly dependent on the profile of the excitation. Micro impedance pump flow studies were conducted in open and closed circuit flow configurations. Maximum flow rates of 16 ml min −1 have been achieved under closed loop flow conditions with an elastic tube diameter of 2 mm. Two size scales with channel diameters of 2 mm and 250 µm were also examined in open circuit flow, resulting in flow rates of 191 µl min −1 and 17 µl min −1 , respectively.

No abstract

In this paper, we analyse the convergence, accuracy and stability of the intrinsic frequency (IF) method. The IF method is a descendant of the sparse time frequency representation methods. These methods are designed for analysing nonlinear and non-stationary signals. Specifically, the IF method is created to address the cardiovascular system that by nature is a nonlinear and non-stationary dynamical system. The IF method is capable of handling specific nonlinear and non-stationary signals with less mathematical regularity. In previous works, we showed the clinical importance of the IF method. There, we showed that the IF method can be used to evaluate cardiovascular performance. In this article, we will present further details of the mathematical background of the IF method by discussing the convergence and the accuracy of the method with and without noise. It will be shown that the waveform fit extracted from the signal is accurate even in the presence of noise.

Childhood cancer survivors are at risk for anthracycline-related cardiac dysfunction, often developing at a time when they are least engaged in long-term survivorship care. New paradigms in survivorship care and chronic disease screening are needed in this population. We compared the accuracy of a novel handheld mHealth platform (Vivio) as well as echocardiography for assessment of cardiac function [left ventricular ejection fraction (EF)] in childhood cancer survivors with cardiac magnetic resonance (CMR) imaging (reference). Cross-sectional study design was used. Concurrent evaluation of EF was performed using Vivio, two-dimensional (2D) echocardiography, and CMR. Differences in mean EF (2D echocardiography vs. CMR; Vivio vs. CMR) were compared using Bland-Altman plots. Linear regression was used to evaluate proportional bias. A total of 191 consecutive survivors participated [50.7% female; median time from diagnosis: 15.8 years (2-44); median anthracycline dose: 225 mg/m (25-642)]. Echocardiography overestimated mean EF by 4.9% ( < 0.001); linear regression analysis confirmed a proportional bias, when compared with CMR ( = 3.1, < 0.001). There was no difference between mean EF derived from Vivio and from CMR (-0.2%, = 0.68). The detection of cardiac dysfunction via echocardiography was poor when compared with CMR [Echo EF< 45% (sensitivity 14.3%), Echo EF < 50% (sensitivity 28.6%)]. Sensitivity was substantially better for Vivio-based measurements [EF < 45% or EF < 50% (sensitivity 85.7%)]. This accessible technology has the potential to change the day-to-day practice of clinicians caring for the large number of patients diagnosed with cardiac dysfunction and heart failure each year, allowing real-time monitoring and management of their disease without the lag-time between imaging and interpretation of results. .