Nonlinear methods of biosignal analysis in assessing terbutaline-induced heart rate and blood pressure changes

Abstract

of biosignal analysis in assessing terbutaline-induced heart rate and blood pressure changes. Am J Physiol Heart Circ Physiol 282: H773-H781, 2002; 10.1152/ajpheart. 00559.2001.-The aim of this study was to characterize how different nonlinear methods characterize heart rate and blood pressure dynamics in healthy subjects at rest. The randomized, placebo-controlled crossover study with intravenous terbutaline was designed to induce four different stationary states of cardiovascular regulation system. The R-R interval, systolic arterial blood pressure, and heart rate time series were analyzed with a set of methods including approximate entropy, sample entropy, Lempel-Ziv entropy, symbol dynamic entropy, cross-entropy, correlation dimension, fractal dimensions, and stationarity test. Results indicate that R-R interval and systolic arterial pressure subsystems are mutually connected but have different dynamic properties. In the drug-free state the subsystems share many common features. When the strength of the baroreflex feedback loop is modified with terbutaline, R-R interval and systolic blood pressure lose mutual synchrony and drift toward their inherent state of operation. In this state the R-R interval system is rather complex and irregular, but the blood pressure system is much simpler than in the drug-free state. nonlinear dynamics; complexity; dimensionality; entropy TRADITIONAL LINEAR ANALYSIS methods of heart rate and blood pressure time series data, such as the time-and frequency-domain methods, measure the strength of oscillations in heart rate and blood pressure within a specific frequency range, for example, in the low-frequency (0.04-0.15 Hz) and high-frequency (0.15-0.4 Hz) bands. The spectral powers obtained can be used, for example, to estimate sympathetic and parasympathetic nervous activity and, with cross-spectral approaches, to characterize arterial baroreflex functions. Generally, the linear methods (time-and frequencydomain methods) are useful and have been widely adopted in studies of health and disease because results from linear methods are quite easy to interpret in physiological terms. But they also have limitations, and criticisms have been raised against their use (5).Multiple feedback loops in cardiovascular regulation systems make rapid adaptations possible under a large variety of physiological and environmental conditions. In analyzing heart rate and blood pressure time series with traditional linear methods, we lose a lot of information on the dynamic patterns used by the cardiovascular regulation systems to adjust heart rate and blood pressure. Linear methods have not been designed to yield information on the systems' inherent dynamic properties. Nonlinear methods of signal analysis can be more useful when characterizing complex dynamics. Thus the idea of using nonlinear statistics in the analysis of heart rate and blood pressure time series data is theoretically very sound and is a challenging objective for both cardiovascular physiologists and system theoreticians. Nonlinear ...

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