Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent.

David Herzig,Robert Riener,Prisca Eser,Ximena Omlin,Peter Achermann,Matthias Wilhelm

doi:10.3389/fphys.2017.01100

Abstract

Objective: Measurements of heart rate variability (HRV) during sleep have become increasingly popular as sleep could provide an optimal state for HRV assessments. While sleep stages have been reported to affect HRV, the effect of sleep stages on the variance of HRV parameters were hardly investigated. We aimed to assess the variance of HRV parameters during the different sleep stages. Further, we tested the accuracy of an algorithm using HRV to identify a 5-min segment within an episode of slow wave sleep (SWS, deep sleep).Methods: Polysomnographic (PSG) sleep recordings of 3 nights of 15 healthy young males were analyzed. Sleep was scored according to conventional criteria. HRV parameters of consecutive 5-min segments were analyzed within the different sleep stages. The total variance of HRV parameters was partitioned into between-subjects variance, between-nights variance, and between-segments variance and compared between the different sleep stages. Intra-class correlation coefficients of all HRV parameters were calculated for all sleep stages. To identify an SWS segment based on HRV, Pearson correlation coefficients of consecutive R-R intervals (rRR) of moving 5-min windows (20-s steps). The linear trend was removed from the rRR time series and the first segment with rRR values 0.1 units below the mean rRR for at least 10 min was identified. A 5-min segment was placed in the middle of such an identified segment and the corresponding sleep stage was used to assess the accuracy of the algorithm.Results: Good reproducibility within and across nights was found for heart rate in all sleep stages and for high frequency (HF) power in SWS. Reproducibility of low frequency (LF) power and of LF/HF was poor in all sleep stages. Of all the 5-min segments selected based on HRV data, 87% were accurately located within SWS.Conclusions: SWS, a stable state that, in contrast to waking, is unaffected by internal and external factors, is a reproducible state that allows reliable determination of heart rate, and HF power, and can satisfactorily be detected based on R-R intervals, without the need of full PSG. Sleep may not be an optimal condition to assess LF power and LF/HF power ratio.

Highlights

There is growing interest for assessments of the activity of the autonomic nervous system (ANS) both in research and in applied settings
The linear trend of rRR time series in the first 4 h was removed and we identified the first period where rRR values were 0.1 units below the mean rRR of the first 4 h for at least 10 min, the same threshold has been used in a previous study (Herzig et al, 2016)
Eighteen healthy male participants with mean age 23.7 ± 2.5 (SD) years were included in the study

Summary

Introduction

There is growing interest for assessments of the activity of the autonomic nervous system (ANS) both in research and in applied settings. Standardized measurements are usually performed during 2–5 min in supine position after resting for at least 10 min at the same time of the day (Camm, 1996). This time requirement may be problematic in situations where regular (daily) measurements are needed, such as monitoring fatigue and training adaptations in athletes (Plews et al, 2014). Resting HRV measurements may be problematic in young children who cannot stay motionless and relaxed on demand

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Conclusion