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Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent
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 investigate...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5767731/ https://www.ncbi.nlm.nih.gov/pubmed/29367845 http://dx.doi.org/10.3389/fphys.2017.01100 |
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author | Herzig, David Eser, Prisca Omlin, Ximena Riener, Robert Wilhelm, Matthias Achermann, Peter |
author_facet | Herzig, David Eser, Prisca Omlin, Ximena Riener, Robert Wilhelm, Matthias Achermann, Peter |
author_sort | Herzig, David |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5767731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57677312018-01-24 Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent Herzig, David Eser, Prisca Omlin, Ximena Riener, Robert Wilhelm, Matthias Achermann, Peter Front Physiol Physiology 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. Frontiers Media S.A. 2018-01-10 /pmc/articles/PMC5767731/ /pubmed/29367845 http://dx.doi.org/10.3389/fphys.2017.01100 Text en Copyright © 2018 Herzig, Eser, Omlin, Riener, Wilhelm and Achermann. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Herzig, David Eser, Prisca Omlin, Ximena Riener, Robert Wilhelm, Matthias Achermann, Peter Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent |
title | Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent |
title_full | Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent |
title_fullStr | Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent |
title_full_unstemmed | Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent |
title_short | Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent |
title_sort | reproducibility of heart rate variability is parameter and sleep stage dependent |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5767731/ https://www.ncbi.nlm.nih.gov/pubmed/29367845 http://dx.doi.org/10.3389/fphys.2017.01100 |
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