Autonomic effects on the spectral analysis of heart rate variability after exercise

Abstract

Although frequency-domain analysis of heart rate variability (HRV) has been performed in the setting of exercise and recovery from exercise, the relationship of specific frequency components to sympathetic and parasympathetic inputs has not been validated in this setting. The aim of this study is to evaluate the relationship of frequency components of HRV to sympathetic and parasympathetic modulation in the setting of recovery after exercise using selective autonomic blockade. Normal subjects (n = 27, 17 men, 53 +/- 7 yr old) underwent bicycle stress testing on four separate days. On day 1, a baseline study without autonomic blockade was performed. On days 2 through 4, either beta-adrenergic, parasympathetic, or double blockade was administered during exercise and completed 3 min before recovery. Continuous ECG was recorded for 5 min starting from the end of exercise. Time- and frequency-domain measures of HRV were computed for each of the five 1-min segments of RR intervals. Parasympathetic blockade significantly decreased all the HRV measures compared with baseline (P < 0.02 for all). Root mean square of successive differences of RR intervals (rMSSD) was increased by beta-adrenergic blockade (P < 0.0002). All the HRV measures except rMSSD showed increases with time after the first minute of recovery. The low frequency-to-high frequency ratio did not respond to autonomic blockade or to recovery time, consistent with the expected changes in sympathovagal influence. Root mean square (detrended SD) and rMSSD were highly correlated with the square root of the total power (r = 0.96) and high-frequency power (r = 0.95), respectively. Although there are marked reductions in the frequency-domain measures in recovery versus rest, the fluctuations in the low- and high-frequency bands respond to autonomic blockade in the expected fashion. Time-domain measures of HRV were highly correlated with frequency-domain measures and therefore provide a computationally more efficient assessment of autonomic influences during recovery from exercise that is less susceptible to anomalies of frequency-domain analysis.