Fractal scaling properties in nonstationary heartbeat time series

Abstract

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long‐range power‐law correlations extending over thousands of heartbeats. This scale‐invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, we find that for subjects at high risk of sudden death (e.g. congestive heart failure patients) these long‐range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiological models of systems that appear to be ‘‘hetero‐dynamic’’ rather than ‘‘homeo‐static.’’