Is slow wave sleep an appropriate recording condition for heart rate variability analysis?

Heart rate variability (HRV) analysis holds increasing interest but electrocardiographic (ECG) recordings are strongly disturbed by body movements, changes in environment and respiration. Here we give arguments for the use of slow wave sleep (SWS) as an appropriate recording condition. Sixteen healthy subjects aged 21–31 years (10 males, 6 females) underwent polygraphic sleep, ECG, and respiratory recordings during one experimental night. HRV was analyzed in 5-min SWS segments and compared to data collected during quiet wake in the morning with controlled breathing, using for each individual the same respiratory frequency as that recorded during SWS. SWS has two major advantages. First, it is a quiet sleep period, free of any external confounding events and is characterized by fewer body movements or arousals that cause abrupt heart rate (HR) increases which disrupt the ECG signal. Second, SWS avoids the deleterious effect of controlled breathing on HRV. Respiratory cycles were spontaneously more regular during SWS than during generally used wake (Standard deviation (SD) of the respiratory cycles was 0.27 ± 0.02 s during SWS vs 0.42 ± 0.07 s during wake under controlled breathing; p < 0.01). Compared to quiet wake, the SD of normal R–R intervals reflecting global variability was significantly lower during SWS (54.3 ± 4.7 vs 78.8 ± 6.1 ms; p < 0.001) and the normalized high frequency power was increased (0.57 ± 0.04 vs 0.51 ± 0.03; p < 0.05), suggesting a higher parasympathetic control of the heart. Thus, SWS offers a “self-controlled” and undisturbed moment of observation for assessing time and frequency domain HRV indexes. Its relevance as an optimal ECG recording condition has to be confirmed in various experimental conditions.