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

Heart rate variability (HRV) is concerned with the analysis of the interval s between heartbeats. An emerging analysis technique is the Poincare plot,. which takes a sequence of intervals and plots each interval against the fo llowing interval. The geometry of this plot has been shown to distinguish b etween healthy and unhealthy subjects in clinical settings. The Poincare pl ot is a valuable HRV analysis technique due to its ability to display nonli near aspects of the interval sequence. The problem is, how do we quantitati vely characterize the plot to capture useful summary descriptors that are i ndependent of existing HRV measures? Researchers have investigated a number of techniques: converting the two-dimensional plot into various one-dimens ional 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 interv als 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 Poincare plot is primarily a nonlinear techn ique. Therefore, further work is needed to determine if better methods of c haracterizing Poincare plot geometry can be found.