Match!

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

Published on Jan 10, 2018in Frontiers in Physiology3.201
· DOI :10.3389/FPHYS.2017.01100
David Herzig5
Estimated H-index: 5
(University of Bern),
Prisca Eser23
Estimated H-index: 23
(University of Bern)
+ 3 AuthorsPeter Achermann59
Estimated H-index: 59
(UZH: University of Zurich)
Abstract
Objective: Measurements of heart rate variability (HRV) during sleep are becoming 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 for 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 RR-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 RR-intervals, without the need of full PSG. Sleep may not be an optimal condition to assess LF power and LF/HF power ratio.
  • References (70)
  • Citations (9)
📖 Papers frequently viewed together
2010EMBC: International Conference of the IEEE Engineering in Medicine and Biology Society
3 Citations
1971
1 Citations
17 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
References70
Newest
#1Hee Nam Yoon (SNU: Seoul National University)H-Index: 11
#2Su Hwan Hwang (SNU: Seoul National University)H-Index: 10
Last. Kwang Suk Park (SNU: Seoul National University)H-Index: 34
view all 6 authors...
We developed an automatic slow-wave sleep (SWS) detection algorithm that can be applied to groups of healthy subjects and patients with obstructive sleep apnea (OSA). This algorithm detected SWS based on autonomic activations derived from the heart rate variations of a single sensor. An autonomic stability, which is an SWS characteristic, was evaluated and quantified using R–R intervals from an electrocardiogram (ECG). The thresholds and the heuristic rule to determine SWS were designed based on...
13 CitationsSource
Background/Aim:There is increasing popularity for athletes to use heart rate variability (HRV) to tailor training. A time-efficient method is HRV assessment during deep sleep. The aim was to validate the selection of deep sleep segments identified by RR-intervals with simultaneous electroencephalography (EEG) recordings and to compare HRV parameters of these segments with those of standard morning supine measurements. Methods:In 11 world class alpine- skiers, RR-intervals were monitored during t...
4 CitationsSource
Purpose:Heart-rate variability (HRV) is a popular tool for monitoring autonomic nervous system status and training adaptation in athletes. It is believed that increases in HRV indicate effective training adaptation, but these are not always apparent in elite athletes. Methods:Resting HRV was recorded in 4 elite rowers (rowers A, B, C, and D) over the 7-wk period before their success at the 2015 World Rowing Championships. The natural logarithm of the square root of the mean sum of the squared di...
17 CitationsSource
#1Kirsty L. Dodds (USYD: University of Sydney)H-Index: 4
#2Christopher B. Miller (USYD: University of Sydney)H-Index: 14
Last. Christopher Gordon (USYD: University of Sydney)H-Index: 14
view all 5 authors...
Summary Heart rate variability (HRV) is an objective marker that provides insight into autonomic nervous system dynamics. There is conflicting evidence regarding the presence of HRV impairment in insomnia patients. Web-based databases were used to systematically search the literature for all studies that compared the HRV of insomnia patients to controls or reported the HRV of insomnia patients before and after an intervention. 22 relevant papers were identified. Study characteristics were summar...
34 CitationsSource
Purpose:To examine which body position and indices present better reliability of heart rate variability (HRV) measures in children and to compare the HRV analyzed in different body positions between sexes. Method:Twenty eutrophic prepubertal children of each sex participated in the study. The RR intervals were recorded using a portable heart rate monitor twice a day for 7 min in the supine, sitting, and standing positions. The reproducibility was analyzed using the intraclass correlation coeffic...
10 CitationsSource
#1Hee Nam Yoon (SNU: Seoul National University)H-Index: 11
#2Su Hwan Hwang (SNU: Seoul National University)H-Index: 10
Last. Kwang Suk Park (SNU: Seoul National University)H-Index: 34
view all 6 authors...
OBJECTIVE: We developed an automatic algorithm to determine rapid eye movement (REM) sleep on the basis of the autonomic activities reflected in heart rate variations. APPROACH: The heart rate variability (HRV) parameters were calculated using the R-R intervals from an electrocardiogram (ECG). A major autonomic variation associated with the sleep cycle was extracted from a combination of the obtained parameters. REM sleep was determined with an adaptive threshold applied to the acquired feature....
11 CitationsSource
#1David Herzig (University of Bern)H-Index: 5
#2Prisca Eser (University of Bern)H-Index: 23
Last. Susi Kriemler (UZH: University of Zurich)H-Index: 39
view all 19 authors...
Background: Recent studies have claimed a positive association of physical activity and body composition on vagal tone. In pediatric populations, there is a pronounced decrease in heart rate with age. While this decrease is often interpreted as an age-related increase in vagal tone, there is some evidence that it may be related to a decrease in intrinsic heart rate. This factor has not been taken into account in most previous studies. The aim of the present study was to assess the effect of phys...
10 CitationsSource
#1Sylvain Laborde (German Sport University Cologne)H-Index: 19
#2Emma Mosley (BU: Bournemouth University)H-Index: 8
Last. Julian F. Thayer (OSU: Ohio State University)H-Index: 77
view all 3 authors...
Psychophysiological research integrating heart rate variability (HRV) has increased during the last two decades, particularly given the fact that HRV is able to index cardiac vagal tone. Vagal tone, which represents the activity of the parasympathetic system, is acknowledged to be linked with many phenomena relevant for psychophysiological research, including self-regulation at the cognitive, emotional, social, and health levels. The ease of HRV collection and measurement coupled with the fact i...
312 CitationsSource
Jan 1, 2017 in BHI (Biomedical and Health Informatics)
#1Xi Long (TU/e: Eindhoven University of Technology)H-Index: 14
#2Pedro Fonseca (TU/e: Eindhoven University of Technology)H-Index: 14
Last. Steffen Leonhardt (RWTH Aachen University)H-Index: 34
view all 6 authors...
Human slow wave sleep (SWS) during bedtime is paramount for energy conservation and memory consolidation. This work aims at automatically detecting SWS from nocturnal sleep using cardiorespiratory signals that can be acquired with unobtrusive sensors in a home-based scenario. From the signals, time-dependent features are extracted for continuous 30-s epochs. To reduce the measuring noise, body motion artifacts, and/or within-subject variability in physiology conveyed by the features and thus enh...
8 CitationsSource
#1Babak Amra (IUMS: Isfahan University of Medical Sciences)H-Index: 12
#2Mohaddeseh Behjati (IUMS: Isfahan University of Medical Sciences)H-Index: 9
Last. Nizal Sarrafzadegan (IUMS: Isfahan University of Medical Sciences)H-Index: 45
view all 6 authors...
Abstract Objectives Heart rate variability (HRV) analysis is used for the evaluation of autonomic function in the cardiovascular system. Decreased HRV is associated with disorders affecting the autonomous system such as diabetes mellitus (DM) and obstructive sleep apnea (OSA). Previous studies have shown an association between OSA and DM. However, the interrelationships of HRV with OSA and DM are not well known. The aim of this study was to assess nocturnal HRV in patients who suffered from OSA ...
3 CitationsSource
Cited By9
Newest
#1Natsuki Nakayama (Nagoya University)H-Index: 3
#1Natsuki Nakayama (Nagoya University)
Last. Makoto Hirai (Sugiyama Jogakuen University)H-Index: 1
view all 6 authors...
This study evaluated the effect of increased physical activity on high-frequency (HF) heart rate variability (HRV) during the first hour after sleep onset in patients with hypertension and/or stabl...
1 CitationsSource
#1Duyan Geng (HEBUT: Hebei University of Technology)
#2Jie Zhao (HEBUT: Hebei University of Technology)
Last. Qi Ning (HEBUT: Hebei University of Technology)
view all 4 authors...
Abstract Heart rate variability (HRV) can reflect the relationship between heart rhythm and sleep structure. In order to achieve long-term effective monitoring of sleep and to solve the generalization problem of sleep staging algorithms, HRV signals were used to identify the wake, non-rapid eye movement (NREM) and rapid eye movement (REM) stages of two databases with 11,597 epoches of 16 subjects (8 healthy subjects and 8 sleep disorder). Features were extracted from HRV using three different me...
Source
Insomnia, i.e. difficulties initiating and/or maintaining sleep, is one of the most common sleep disorders. To study underlying mechanisms for insomnia, we studied autonomic activity changes around sleep onset in participants without clinical insomnia but with varying problems with initiating or maintaining sleep quantified as increased sleep onset latency (SOL) and wake after sleep onset (WASO) respectively. Polysomnography and electrocardiography were simultaneously recorded in 176 participant...
Source
#1Reza Sadeghi (Wright State University)H-Index: 5
#2Tanvi Banerjee (Wright State University)H-Index: 13
Last. Larry Wayne Lawhorne (Wright State University)H-Index: 15
view all 4 authors...
Abstract Most caregivers of people with dementia (CPWD) experience a high degree of stress due to the demands of providing care, especially when addressing unpredictable behavioral and psychological symptoms of dementia. Such challenging responsibilities make caregivers susceptible to poor sleep quality with detrimental effects on their overall health. Hence, monitoring caregivers’ sleep quality can provide important CPWD stress assessment. Most current sleep studies are based on polysomnography...
Source
#1Kimberly A. BellH-Index: 4
#2Ihori Kobayashi (HU: Howard University)H-Index: 13
Last. Thomas A. Mellman (HU: Howard University)H-Index: 30
view all 5 authors...
Abstract Background Heightened autonomic nervous system (ANS) arousal is a well-established contributor to the effect of stress on adverse cardiovascular health outcomes which disproportionately affect African Americans. ANS arousal is normally attenuated during sleep and compromise of this shift is associated with multiple adverse cardiovascular outcomes. Parasympathetic nervous system (PNS) dominance during sleep can be altered by stress. Racism has been recognized to have many negative health...
1 CitationsSource
#1Sanae Oriyama (Hiroshima University)H-Index: 3
#2Yukiko Miyakoshi (Nihon Fukushi University)H-Index: 1
Last. Moshiur Rahman (Hiroshima University)H-Index: 3
view all 3 authors...
OBJECTIVE: To investigate sleepiness, fatigue, and performance following a 120-minute nap during simulated 16-hour night shifts based on subjective and objective assessments. METHODS: Fourteen females participated in this crossover comparative study. Three experimental nap conditions were used: naps from 22:00 to 00:00 (22-NAP), 00:00 to 02:00 (00-NAP), and 02:00 to 04:00 (02-NAP), respectively. Measurement items were sleep parameters, sublingual temperature, a Visual Analog Scale for sleepiness...
1 CitationsSource
#1Sylvain Laborde (German Sport University Cologne)H-Index: 19
#2Thomas Hosang (Helmut Schmidt University)H-Index: 2
Last. Fabrice Dosseville (UNICAEN: University of Caen Lower Normandy)H-Index: 13
view all 4 authors...
Breathing techniques are part of traditional relaxation methods; however, their influence on psychophysiological variables related to sleep is still unclear. Consequently, the aim of this paper was to investigate the influence of a 30-day slow-paced breathing intervention compared to social media use on subjective sleep quality and cardiac vagal activity (CVA, operationalized via high-frequency heart rate variability). Healthy participants (n = 64, 33 male, 31 female, M = 22.11, SD = 3.12) were ...
7 CitationsSource
Objective: To demonstrate the utility of rheoencephalography (REG) for measuring cerebral blood flow and fluid dynamics during different stages of sleep. Methods: Anteroposterior cranial electrical impedance was measured with concurrent polysomnography in a group of healthy subjects during sleep. Transcranial electrical impedance was characterized by measuring the peak-to-trough and envelope of the filtered pulsative REG signal as well as its frequency. The sensitivity of the REG amplitude to ch...
1 CitationsSource
#1Christi S. Ulmer (Duke University)H-Index: 16
#2Martica Hall (University of Pittsburgh)H-Index: 57
Last. Anne Germain (University of Pittsburgh)H-Index: 40
view all 5 authors...
Study Objectives: To determine whether high-frequency heart rate variability (HF-HRV) during sleep differs between those with and without posttraumatic stress disorder (PTSD) as a function of sleep type (non-rapid eye movement [NREM] vs. rapid eye movement [REM]), and to explore this relationship across successive sleep cycles. Participants with PTSD were hypothesized to have lower HF-HRV across both REM and NREM sleep. Methods: Sixty-two post-9/11 military veterans and service members completed...
12 CitationsSource