Heart rate variability, sleep and sleep disorders

Stein, Phyllis K.; Pu, Yachuan

doi:10.1016/j.smrv.2011.02.005

Cited by 391 publications

(326 citation statements)

References 71 publications

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“…(5, 9, 13) Accordingly, the research focus has shifted to investigating the associations between HRV, sleep disorders and their subsequent comorbidities and the incorporation of non-traditional HRV techniques. (5,13,14) Given the interplay between HRV and cardiac autonomic activity, the use of HRV in insomnia research may assist further investigation into the pathophysiology and potential health impacts of insomnia. Hyperarousal has been defined as 'a state of increased arousal at the physiological, cortical, cognitive or emotional level' (15) and hypothesised to contribute to the development, maintenance and 24-hour systemic sequelae of insomnia.…”

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confidence: 99%

“…(20) However, the extant research literature has not been able to replicate these findings with comparable detail and instead yielded somewhat inconsistent, divergent findings. (21) Whilst two reviews examining HRV, sleep and sleep disorders have been published previously they did not systematically synthesise the findings of the insomnia -HRV literature and we were aware of additional studies that were not included (5,13). Therefore, the aim of this review was to identify all HEART RATE VARIABILITY IN INSOMNIA PATIENTS …”

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confidence: 99%

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Heart rate variability in insomnia patients: A critical review of the literature

Dodds

Miller

Kyle

et al. 2017

Sleep Medicine Reviews

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SummaryHeart 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 summarised, HRV measures were extracted and a risk of bias assessment for each study was performed. We were limited in our ability to synthesise outcome measures and perform metaanalyses due to considerable differences in patient (and control) selection, study protocols, measurement and processing techniques and outcome reporting. Risk of bias was deemed to be high in the majority of studies. As such, we cannot confirm that HRV is reliably impaired in insomnia patients nor determine the HRV response to interventions. Whilst HRV impairment in insomnia is a widely accepted concept, it is not supported by empirical evidence. Large longitudinal studies incorporating 24-hour recordings are required to elucidate the precise nature of HRV dynamics in insomnia patients. Key Wordsautonomic nervous system, heart rate variability, hyperarousal, insomnia, review HEART RATE VARIABILITY IN INSOMNIA PATIENTS

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Section: Insert Table 1 About Herementioning

confidence: 99%

Section: Insert Table 1 About Herementioning

confidence: 99%

Heart rate variability in insomnia patients: A critical review of the literature

Dodds

Miller

Kyle

et al. 2017

Sleep Medicine Reviews

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“…15 HR is influenced by the combined effects of both branches of the ANS, the sympathetic and parasympathetic nervous system. HRV measurements provide information about the function of the ANS 16 and are derived from mathematical analyses of the R-R intervals during normal sinus rhythm in the electrocardiogram (ECG). High-frequency HRV (HF-HRV) measures represent parasympathetic influences under normal circumstances, 16 whereas low-frequency HRV (LF-HRV) measures represent both sympathetic and parasympathetic modulation.…”

Section: Significancementioning

confidence: 99%

“…HRV measurements provide information about the function of the ANS 16 and are derived from mathematical analyses of the R-R intervals during normal sinus rhythm in the electrocardiogram (ECG). High-frequency HRV (HF-HRV) measures represent parasympathetic influences under normal circumstances, 16 whereas low-frequency HRV (LF-HRV) measures represent both sympathetic and parasympathetic modulation. 17 Decreased parasympathetic modulation has been associated with an increased risk for CVD and early mortality in a community sample, 18 and mortality after MI.…”

Section: Significancementioning

confidence: 99%

Sleep Duration and Quality in Relation to Autonomic Nervous System Measures: The Multi-Ethnic Study of Atherosclerosis (MESA)

Castro‐Diehl

Roux

Redline

et al. 2016

Sleep

136

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Study Objectives: Short sleep duration and poor sleep quality are associated with adverse cardiovascular outcomes. Potential pathophysiological mechanisms include sleep-associated alterations in the autonomic nervous system. The objective of this study was to examine the associations of shorter sleep duration and poorer sleep quality with markers of autonomic tone: heart rate (HR), high-frequency HR variability (HF-HRV) and salivary amylase. Methods: Cross-sectional analysis of data from actigraphy-based measures of sleep duration and efficiency and responses to a challenge protocol obtained from 527 adult participants in the Multi-Ethnic Study of Atherosclerosis. Results: Participants who slept fewer than 6 h per night (compared to those who slept 7 h or more per night) had higher baseline HR (fully adjusted model 0.05 log beats/min, 95% confidence interval [CI] 0.01, 0.09) and greater HR orthostatic reactivity (fully adjusted model 0.02 log beats/min, 95% CI 0.002, 0.023). Participants who slept 6 to less than 7 h/night (compared to those who slept 7 h or more per night) had lower baseline HF-HRV (fully adjusted model −0.31 log msec 2 , 95% CI −0.60, −0.14). Participants with low sleep efficiency had lower baseline HF-HRV than those with higher sleep efficiency (fully adjusted model −0.59 log msec 2 , 95% CI −1.03, −0.15). Participants with low sleep efficiency had higher baseline levels of amylase than those with higher sleep efficiency (fully adjusted model 0.45 log U/mL, 95% CI 0.04, 0.86). Conclusions: Short sleep duration, low sleep efficiency, and insomnia combined with short sleep duration were associated with markers of autonomic tone that indicate lower levels of cardiac parasympathetic (vagal) tone and/or higher levels of sympathetic tone.

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“…In addition, it is reported that heart rate and HRV progressively decrease during non-REM sleep and increase during REM sleep [11].…”

Section: Heart Rate Variability and Drowsinessmentioning

confidence: 99%

Development of Drowsiness Detection Method by Integrating Heart Rate Variability Analysis and Multivariate Statistical Process Control

Abe

Fujiwara

Hiraoka

et al. 2016

SICE Journal of Control, Measurement, and System Integration

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: Drowsy driving accidents can be prevented if predicted in advance. The present work aims to develop a new method for detecting driver drowsiness based on the fact that the autonomic nervous function affects heart rate variability (HRV), which is a fluctuation of the RR interval (RRI) obtained from an electrocardiogram (ECG). The proposed method uses eight HRV features derived through HRV analysis as input variables of multivariate statistical process control (MSPC), which is a well-known anomaly detection method in the field of process control. In the proposed method, only one principal component was adopted in MSPC and driver drowsiness was detected through monitoring the T 2 statistic. Driving simulator experiments demonstrated that driver drowsiness was successfully detected in seven out of eight cases before accidents occurred. In addition, the proposed method was implemented in a smartphone app for on-vehicle use.

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Heart rate variability, sleep and sleep disorders

Cited by 391 publications

References 71 publications

Heart rate variability in insomnia patients: A critical review of the literature

Heart rate variability in insomnia patients: A critical review of the literature

Sleep Duration and Quality in Relation to Autonomic Nervous System Measures: The Multi-Ethnic Study of Atherosclerosis (MESA)

Development of Drowsiness Detection Method by Integrating Heart Rate Variability Analysis and Multivariate Statistical Process Control

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