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

G. D'Addio, G. D. Pinna, R. Maestri, G. Corbi, N. Ferrara, F. Rengo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Poincarè 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.

Original languageEnglish
Title of host publicationComputers in Cardiology
EditorsA. Murray
Pages457-460
Number of pages4
Volume31
Publication statusPublished - 2004
EventComputers in Cardiology 2004 - Chicago, IL, United States
Duration: Sep 19 2004Sep 22 2004

Other

OtherComputers in Cardiology 2004
CountryUnited States
CityChicago, IL
Period9/19/049/22/04

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Software

Fingerprint Dive into the research topics of 'Quantitative Poincare plots analysis contains relevant information related to heart rate variability dynamics of normal and pathological subjects'. Together they form a unique fingerprint.

  • Cite this