Frequency-domain characteristics and filtering of blood flow following the onset of exercise: implications for kinetics analysis

Abstract

We examined the validity and usefulness of a low-pass filter (LPFILTER) to reduce point-to-point variability and enhance parameter estimation of the kinetics of blood flow (BF). Computer simulations were used to determine the power spectrum of simulated responses. Moreover, we studied the leg BF response to a single transition in four subjects during supine knee-extension exercise using three methods of data processing [beat-by-beat, average of 3 cardiac cycles (AVG3 BEATS), and LPFILTER]. The power spectrum of BF containing the kinetics information (≤0.2 Hz) did not overlap with the oscillations due to muscle contraction and cardiac cycle (simulations and Doppler measurements). There were no significant differences between the parameter estimates for a two-exponential model using Beat-by-Beat, AVG3 BEATS, and LPFILTER ( P > 0.05; n = 4). However, LPFILTER (cutoff = 0.2 Hz) resulted in a significantly lower standard error of the estimate for all parameters ( P < 0.05). The means ± SD for the standard error of the estimate for Beat-by-Beat, AVG3 BEATS, and LPFILTER were, respectively, time constant- phase 1 = 5.0 ± 1.1 s, 4.5 ± 2.1 s, and 0.3 ± 0.2 s; time delay- phase 2 = 17.8 ± 7.9 s, 12.8 ± 7.5 s, and 1.4 ± 1.4 s; time constant- phase 2 = 15.8 ± 4.6 s, 9.9 ± 2.9 s, and 1.1 ± 0.5 s. In conclusion, LPFILTER appeared to be a valid procedure providing a high signal-to-noise ratio and data density and thus LPFILTER resulted in the smallest confidence interval for parameter estimates of BF kinetics.