2005•Unpublished venueRequires access

New insights into the relationship between Poincare plot geometry and linear measures of heart rate variability

Michael Brennan, Marimuthu Swami Palaniswami, Peter Walter Kamen

Open publisher page 18 citations

Abstract

The Poincare plot is an emerging Heart Rate Variability (HRV) analysis technique, the geometry of which has been shown to distinguish between healthy and unhealthy subjects in clinical settings. The Poincare plot is able to display nonlinear aspects of the interval sequence and is therefore of interest in characterizing the nonlinear aspects of HRV. The problem is, how do we quantitatively characterize the geometry of the plot to capture useful descriptors that are independent of existing HRV measures? In this paper, we investigate a popular existing category of techniques and show that they measure linear aspects of the intervals which existing HRV indices 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 technique.

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What this paper is about

The Poincare plot is an emerging Heart Rate Variability (HRV) analysis technique, the geometry of which has been shown to distinguish between healthy and unhealthy subjects in clinical settings. The Poincare plot is able to display nonlinear aspects of the interval sequence and is therefore of interest in characterizing the nonlinear aspects of HRV. The problem is, how do we quantitatively characterize the geometry of the plot to capture useful descriptors that are independent of existing HRV measures? In this paper, we investigate a popular existing category of techniques and show that they measure linear aspects of the intervals which existing HRV indices 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 technique.

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Available abstract

The Poincare plot is an emerging Heart Rate Variability (HRV) analysis technique, the geometry of which has been shown to distinguish between healthy and unhealthy subjects in clinical settings. The Poincare plot is able to display nonlinear aspects of the interval sequence and is therefore of interest in characterizing the nonlinear aspects of HRV. The problem is, how do we quantitatively characterize the geometry of the plot to capture useful descriptors that are independent of existing HRV measures? In this paper, we investigate a popular existing category of techniques and show that they measure linear aspects of the intervals which existing HRV indices 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 technique.

Key concepts: Poincaré plot, Plot (graphics), Nonlinear system, Poincaré conjecture, Recurrence plot, Heart rate variability, Mathematics, Measure (data warehouse)

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