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Heart rate variability (HRV) analysis uses variations in heart rate to assess activity of the autonomic nervous system. Ectopic beats can affect HRV by introducing mathematical artifact into the computations of time- and frequency-domain measures. Exclusion of ectopy-containing segments of data from analysis has been used to correct for ectopy, but this technique eliminates data and may bias HRV measurements if ectopic beats are causally associated with changes in autonomic tone. We have assessed algorithms for correcting for ectopy: deletion, in which ectopic beats are removed from the R-R sequence; linear and cubic spline interpolation; and nonlinear predictive interpolation, in which ectopy-free R-R sequences are used as templates for replacing ectopic beats. The null method (no ectopy correction) was evaluated to determine the importance of ectopy correction. These methods were applied to computer-generated sequences created by adding simulated ventricular premature depolarizations to 5-min ectopy-free R-R sequences. The null method resulted in significant alterations in HRV. Deletion and nonlinear predictive interpolation performed superiorly to linear or cubic spline interpolation, which overestimated low-frequency power and underestimated high-frequency power. Thus ectopy correction is necessary for HRV analysis; deletion of ectopic beats performs as well as or better than more complicated methods for these relatively short data samples.
Lippman et al. (Fri,) studied this question.