Heart rate variability: measurement error or chaos

Guidelines published for the spectral analysis of heart rate variability (HRV) offer little insight into the handling of a fundamental error source, namely sampling frequency (f_s) measurement error. Using artificial heart rate data we systematically examined the effect that f_s and modulating amplitudes have on the power spectrum of HRV data. The derived topological information forms the basis for developing criteria which determine whether a recorded R-R signal has a high enough signal to noise ratio to perform spectral analysis within a confidence interval of ±15%. These criteria are tested using R-R interval data obtained with f_s values ranging between 31.25-500 Hz in four patients with differing HRV profiles. This paper presents the results of both model simulations and actual data, showing how the effect of f_s measurement error can be described in terms of nonlinear dynamics