Short- and Long-Term Statistical Properties of Heartbeat Time-Series in Healthy and Pathological Subjects

TL;DR

This study investigates heartbeat time-series across various health conditions, revealing persistent long-range correlations in most subjects and distinct short-term properties in healthy and certain patient groups.

Contribution

It introduces an information-based technique to detect long-range correlations and compares short- and long-term statistical behaviors across different health conditions.

Findings

Long-range correlations are common in healthy and some patient groups.

CHF individuals often lack these long-range correlations.

Healthy subjects exhibit specific short-term properties absent in transplanted patients.

Abstract

We analize heartbeat time-series corresponding to several groups of individuals (healthy, heart transplanted, with congestive heart failure (CHF), after myocardial infarction (MI), hypertensive), looking for short- and long-time statistical behaviors. In particular we study the persistency patterns of interbeat times and interbeat-time variations. Long-range correlations are revealed using an information-based technique which makes a wise use of the available statistics. The presence of strong long-range time correlations seems to be a general feature for all subjects, with the exception of some CHF individuals. We also show that short time-properties detected in healthy subjects, and seen also in hypertensive and MI patients, and completely absent in the trasplanted, are characterized by a general behavior when we apply a proper coarse-graining procedure for time series analysis.