Potential force dynamics of heart rate variability reflect cardiac autonomic modulation with respect to posture, age, and breathing pattern
Various physiological and pathological conditions are correlated with cardiac autonomic function. Heart rate variability is a marker of cardiac autonomic modulation and can be measured by several methods. However, the available methods are sensitive to breathing patterns. To quantify cardiac autonomic modulation by observing the potential force dynamics of the R?R interval time series in healthy individuals. We propose two potentials of unbalanced complex kinetic (PUCK) parameters to quantify the characteristics of the potential force dynamics of R?R interval time series: potential strength (slope) and fluctuation size (slope standard deviations [SSD1, SSD2]). We applied this method to the series of R?R intervals obtained from 30 healthy subjects in an experimental condition that elicited cardiac autonomic (i.e., sympathetic and vagal) activation (in supine, sitting, and standing positions). Subjects were categorized into three groups by decade (i.e., 20s, 30s, and 40s) to verify the cardiac autonomic differences by age. Two respiration patterns were introduced to check the influence of the pattern into the analytical results. Sympathetic modulation activation significantly increased the slope and reduced SSD1 and SSD2; these trends were confirmed in all groups. The slope is concordant with the result of the low frequency/high frequency (LF/HF) ratio in frequency components as an indicator of sympathetic modulation. No trend was observed in slope among age groups. However, SSD1 and SSD2 in the 40s group were significantly decreased in the supine and sitting positions. The results with respect to respiration frequency showed lower sympathetic modulation as shown in the LF/HF ratio and slope, whereas higher vagal modulation as shown in the HF appeared with a longer breathing rate. PUCK can quantify the cardiac autonomic modulation in the experimental conditions of different postures. SSD1 and SSD2 are more sensitive to age than frequency components and are unaffected by breathing patterns. This method may be an alternative method for observing cardiac autonomic modulation in clinical practice.
potential force dynamics heart rate variability breathing pattern non-linear analysis autonomic nervous system