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Receiver-operating-characteristic (ROC) analysis was used to assess thesuitability of various heart rate variability (HRV) measures for correctlyclassifying electrocardiogram records of varying lengths as normal or revealingthe presence of heart failure. Scale-dependent HRV measures were found to besubstantially superior to scale-independent measures (scaling exponents) fordiscriminating the two classes of data over a broad range of record lengths.The wavelet-coefficient standard deviation at a scale near 32 heartbeatintervals, and its spectral counterpart near 1/32 cycles per interval, providereliable results using record lengths just minutes long. A jitteredintegrate-and-fire model built around a fractal Gaussian-noise kernel providesa realistic, though not perfect, simulation of heartbeat sequences.

Receiver-Operating-Characteristic Analysis Reveals Superiority of Scale-Dependent Wavelet and Spectral Measures for Assessing Cardiac Dysfunction