Quantitative poincare plots analysis contains relevant information related to heart rate variability dynamics of normal and pathological subjects

Poincar plots (PPlots) analysis of RR time series allows a beat-to-beat approach to HRV, detecting patterns associated with non linear processes. Aim of this study was to assess the discriminating power of this method over fifty 24-hours Holter recordings of normal, hypertensive, post-MI, chronic heart failure and transplanted subjects. The analysis was performed by nine novel computer-generated quantitative descriptors of main 2D and 3D morphological characteristics of PPlots. A forward stepwise discriminant analysis showed that four variables, provided independent and significant contribution to the overall discrimination with a 82% total classification function's score between different pathological conditions. Although further investigations should be provided, this results clearly indicate that PPlots analysis contains relevant information related to different HRV dynamics of normal and cardiac patients.