Deceleration capacity (DC) of heart rate is a novel index for evaluating the activity of the autonomic nervous system (ANS). We examined whether controlling the inspiration/expiration (I/E) ratio benefits the DC analysis based on a model-generated RR interval (RRI)database
IntroductionDeceleration capacity (DC) and acceleration capacity (AC) of heart rate are a pair of novel indices for the evaluation of autonomic nervous system (ANS) [1]. They are obtained by applying a phase-rectified signal averaging (PRSA) algorithm to the RR interval (RRI) series [2]. The PRSA selects the decelerating or the accelerating RRIs as the anchor points. The sections around the anchor points are defined and averaged to produce an averaging RRI series. DC or AC is computed as the coefficient of the Haar wavelet at scale two in the center of the averaging RRI series.The performances of DC and AC are distinct [1,3,4]. Based on a cardiovascular system model, we recently demonstrated that the degree of heart rate asymmetry (HRA) influences the performance of DC and AC in assessing the activity of ANS [5]. It implies that the performance of DC can be improved by adjusting the HRA level. As the inspiration/expiration (I/E) ratio influences the HRA level [6,7], we attempted to analyze whether controlling the I/E ratio benefits DC in assessing the ANS activity.Our study was conducted based on a cardiovascular system model. The model can produce a set of RRI time series with controlled levels of ANS activity for DC calculation. It can also control the I/E ratio to examine its role in the performance of DC..
MethodsThe study was conducted in three steps. First, we developed the cardiovascular system model to simulate the RRI time series. Second, we generated a set of RRI time series with random ANS activities and controlled respiratory I/E ratios as the virtual subjects for the study. Third, we computed DC for all the subjects and analyzed the performance of DC under different respiratory patterns.
Model developmentThe block diagram of the cardiovascular system model is shown in Figure 1. Details of the model can be referred in the literature [8,9]. It contains a hemodynamic model