Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability?

TLDR

Heart rate variability (HRV) analysis uses the intervals between heartbeats, and the Poincaré plot, which graphs each interval against the next, has been shown to distinguish healthy from unhealthy subjects by revealing nonlinear aspects of the interval sequence. The study seeks to identify quantitative descriptors of Poincaré plot geometry that capture useful summary information independent of existing HRV measures, and to determine whether improved characterization methods can be developed. Researchers examined several techniques—transforming the two‑dimensional plot into one‑dimensional views, fitting an ellipse to the plot shape, and computing the plot’s correlation coefficient—to quantify its geometry. All examined methods were found to measure linear aspects of the intervals already captured by existing HRV indices, revealing that these descriptors are insensitive to the plot’s nonlinear characteristics, a key limitation of the Poincaré approach.

Abstract

Heart rate variability (HRV) is concerned with the analysis of the intervals between heartbeats. An emerging analysis technique is the Poincaré plot, which takes a sequence of intervals and plots each interval against the following interval. The geometry of this plot has been shown to distinguish between healthy and unhealthy subjects in clinical settings. The Poincaré plot is a valuable HRV analysis technique due to its ability to display nonlinear aspects of the interval sequence. The problem is, how do we quantitatively characterize the plot to capture useful summary descriptors that are independent of existing HRV measures? Researchers have investigated a number of techniques: converting the two-dimensional plot into various one-dimensional views; the fitting of an ellipse to the plot shape; and measuring the correlation coefficient of the plot. We investigate each of these methods in detail and show that they are all measuring linear aspects of the intervals which existing HRV indexes already specify. The fact that these methods appear insensitive to the nonlinear characteristics of the intervals is an important finding because the Poincaré plot is primarily a nonlinear technique. Therefore, further work is needed to determine if better methods of characterizing Poincaré plot geometry can be found.