Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent

Heart rate variability during sleep onset in patients with insomnia with or without comorbid sleep apnea

OBJECTIVES

Pre-sleep stress or hyperarousal is a known key etiological component in insomnia disorder. Despite this, physiological alterations during the sleep onset are not well-understood. In particular, insomnia and obstructive sleep apnea (OSA) are highly prevalent co-morbid conditions, where autonomic regulation may be altered. We aimed to characterize heart rate variability (HRV) during sleep onset as a potential measure of pre-sleep hyperarousal.

METHODS

We described the profile of pre-sleep HRV measures and explore autonomic differences in participants with self-reported insomnia disorder (with no OSA, n = 69; with mild OSA, n = 70; with moderate or severe OSA, n = 66), compared to normal sleep controls (n = 123). Heart rate data during the sleep onset process were extracted for HRV analyses.

RESULTS

During the sleep onset process, compared to normal sleep controls, participants with insomnia had altered HRV, indicated by higher heart rate (p = 0.004), lower SDNN (p = 0.003), reduced pNN20 (p < 0.001) and pNN50 (p = 0.010) and lower powers (p < 0.001). Participants with insomnia and moderate/severe OSA may have further deteriorated HRV outcomes compared to no/mild OSA patients with insomnia but differences were not significant. Insomnia itself was associated with significantly higher heart rate, lower pNN20, and lower high frequency power even after adjustment for age, gender, BMI and OSA severity.

CONCLUSIONS

Participants with insomnia had lower vagal activity during the sleep onset period, which may be compounded by OSA, reflected in higher heart rates and lower HRV. These altered heart rate dynamics may serve as a physiological biomarker for insomnia during bedtime wakefulness, or as a potential tool to evaluate the efficacy of behavioral interventions which target bedtime stress.

Vortioxetine's impact on the autonomic nervous system in depressed children and adolescents: analysis of the heart rate variability

Relationship between depressive disorder and autonomic nervous system has been already discussed. Reduced emotional regulation is supposed to be associated with prefrontal hypofunction and subcortical hyperactivity. The aim of this study was to determine the effect of vortioxetine on heart rate variability (HRV), a parameter of cardiac autonomic regulation, in depressed hospitalized paediatric patients and assess the clinical effectiveness of the drug in this population. We performed repeated polysomnography analyses at admission and after a short treatment in hospital (15.2 days on average) and measured various HRV parameters (RRi, pNN50, RMSSD, LF-HRV, HF-HRV) during wakefulness, N3 and REM sleep stages. Out of 27 study subjects, 67% have improved depression symptoms as well as anxiety and subjective sleep quality after short vortioxetine treatment. We have found a significant decrease in parasympathetic parameters pNN50, RMSSD and HF-HRV during N3 sleep phase, though not exclusively among vortioxetine responders. The anticipated increase in cardiovagal regulation after vortioxetine treatment was not demonstrated in this pilot study, possibly due to the drug's multimodal mechanism and impact on the nucleus tractus solitarii, particularly its antagonism on 5HT-3 receptors. Application of selective drugs could further explain the effect of vortioxetine on HRV in depressed patients.

Evaluation of Autonomic Nervous System Function During Sleep by Mindful Breathing Using a Tablet Device: Randomized Controlled Trial

BACKGROUND

One issue to be considered in universities is the need for interventions to improve sleep quality and educational systems for university students. However, sleep problems remain unresolved. As a clinical practice technique, a mindfulness-based stress reduction method can help students develop mindfulness skills to cope with stress, self-healing skills, and sleep.

OBJECTIVE

We aim to verify the effectiveness of mindful breathing exercises using a tablet device.

METHODS

In total, 18 nursing students, aged 18-22 years, were randomly assigned and divided equally into mindfulness (Mi) and nonmindfulness (nMi) implementation groups using tablet devices. During the 9-day experimental period, cardiac potentials were measured on days 1, 5, and 9. In each sleep stage (sleep with sympathetic nerve dominance, shallow sleep with parasympathetic nerve dominance, and deep sleep with parasympathetic nerve dominance), low frequency (LF) value, high frequency (HF) value, and LF/HF ratios obtained from the cardiac potentials were evaluated.

RESULTS

On day 5, a significant correlation was observed between sleep duration and each sleep stage in both groups. In comparison to each experimental day, the LF and LF/HF ratios of the Mi group were significantly higher on day 1 than on days 5 and 10. LF and HF values in the nMi group were significantly higher on day 1 than on day 5.

CONCLUSIONS

The correlation between sleep duration and each sleep stage on day 5 suggested that sleep homeostasis in both groups was activated on day 5, resulting in similar changes in sleep stages. During the experimental period, the cardiac potentials in the nMi group showed a wide range of fluctuations, whereas the LF values and LF/HF ratio in the Mi group showed a decreasing trend over time. This finding suggests that implementing mindful breathing exercises using a tablet device may suppress sympathetic activity during sleep.

TRIAL REGISTRATION

UMIN-CTR Clinical Trials Registry UMIN000054639; https://tinyurl.com/mu2vdrks.

Is boredom at work bad for your health? Examining the links between job boredom and autonomic nervous system dysfunction

Job boredom refers to an unpleasant state of passiveness at work that has been found to negatively relate to self-reported health. To date, however, the relation between job boredom and physiological indicators of health has not been examined. The present study investigates whether job boredom relates to dysfunction in autonomic nervous system (ANS) activity as indicated by reduced heart rate variability (HRV) during night sleep. The sample of this study consisted of Finnish public sector workers (n = 125). Job boredom was assessed with an electronic questionnaire and HRV with an ambulatory monitoring period of two nights of sleep. The results supported the hypothesis by showing a negative relation between job boredom and HRV, after controlling for demographic and lifestyle factors. The findings extend previous knowledge on the detrimental consequences of job boredom by showing that it is related to dysfunction in ANS activity. Consequently, it is important to acknowledge boredom at work as a threat to occupational health and well-being and pay more attention to how it can be prevented at workplaces.

Exploring sleep heart rate variability: linear, nonlinear, and circadian rhythm perspectives

Background

Heart rate variability (HRV) is believed to possess the potential for disease detection. However, early identification of heart disease remains challenging, as HRV analysis in dogs primarily reflects the advanced stages of the disease.

Hypothesis/objective

The aim of this study is to compare 24-h HRV with sleep HRV to assess the potential utility of sleep HRV analysis.

Animals

Thirty healthy dogs with no echocardiographic abnormalities were included in the study, comprising 23 females and 7 males ranging in age from 2 months to 8 years (mean [standard deviation], 1.4 [1.6]).

Methods

This study employed a cross-sectional study. 24-h HRV and sleep HRV were measured from 48-h Holter recordings. Both linear analysis, a traditional method of heart rate variability analysis, and nonlinear analysis, a novel approach, were conducted. Additionally, circadian rhythm parameters were assessed.

Results

In frequency analysis of linear analysis, the parasympathetic index nHF was significantly higher during sleep compared to the mean 24-h period (mean sleep HRV [standard deviation] vs. mean 24 h [standard deviation], 95% confidence interval, p value, r-family: 0.24 [0.057] vs. 0.23 [0.045], 0.006-0.031, p = 0.005, r = 0.49). Regarding time domain analysis, the parasympathetic indices SDNN and RMSSD were also significantly higher during sleep (SDNN: 179.7 [66.9] vs. 156.6 [53.2], 14.5-31.7, p < 0.001, r = 0.71 RMSSD: 187.0 [74.0] vs. 165.4 [62.2], 13.2-30.0, p < 0.001, r = 0.70). In a geometric method of nonlinear analysis, the parasympathetic indices SD1 and SD2 showed significantly higher values during sleep (SD1: 132.4 [52.4] vs. 117.1 [44.0], 9.3-21.1, p < 0.001, r = 0.70 SD2: 215.0 [80.5] vs. 185.9 [62.0], 17.6-40.6, p < 0.001, r = 0.69). Furthermore, the circadian rhythm items of the parasympathetic indices SDNN, RMSSD, SD1, and SD2 exhibited positive peaks during sleep.

Conclusion

The findings suggest that focusing on HRV during sleep can provide a more accurate representation of parasympathetic activity, as it captures the peak circadian rhythm items.

Association of intra-shift nap duration with heart rate variability in medical night shift workers

Napping during night shifts effectively reduces disease risk and improves work performance, but few studies have investigated the association between napping and physiological changes, particularly in off-duty daily lives. Changes in the autonomic nervous system precede diseases like cardiovascular disease, diabetes, and obesity. Heart rate variability is a good indicator of autonomic nervous system. This study aimed to investigate the link between night shift nap durations and heart rate variability indices in the daily lives of medical workers. As indicators of chronic and long-term alterations, the circadian patterns of heart rate variability indices were evaluated. We recruited 146 medical workers with regular night shifts and divided them into four groups based on their self-reported nap durations. Heart rate variability circadian parameters (midline-estimating statistic of rhythm, amplitude, and acrophase) were obtained by obtaining 24-h electrocardiogram on a day without night shifts, plotting the data of the heart rate variability indices as a function of time, and fitting them into periodic cosine curves. Using clinical scales, depression, anxiety, stress, fatigue, and sleepiness were assessed. Linear regression analysis revealed a positive relationship between 61-120-min naps and 24-h, daytime, and night-time heart rate variability indices, and the parasympathetic activity oscillation amplitude (indexed by high-frequency power, the square root of the mean of the sum of squares of differences between adjacent normal intervals, standard deviation of short-term R-R-interval variability) within one circadian cycle. This study indicated that napping for 61-120 min during night shifts could benefit medical workers' health, providing physiological evidence to promote nap management.

Heart Rate and Heart Rate Variability in Healthy Preterm-Born Young Adults and Association with Vitamin D: A Wearable Device Assessment

Prematurity has been associated with impaired parasympathetic cardiac regulation later in life. Changes in heart rate (HR) and heart rate variability (HRV) may indicate a risk for future cardiac dysfunction. The putative role of Vitamin D on cardiac autonomic function in individuals born preterm (PT) remains unknown. This study involves monitoring autonomic cardiac regulation and Vitamin D concentrations in 30 PT and 16 full-term (FT) young adults in a free-living context. The PT subjects were born between 1994 and 1997 at Oulu University Hospital. The inclusion criteria were (1) being born ≤ 32 gestation weeks or (2) being born < 34 gestation weeks with a birth weight under 1500 g. Participants wore an Oura ring sleep tracer, a smart ring device, for 2 weeks to monitor cardiac autonomic function. Parameters related to autonomic cardiac regulation, lowest nighttime resting HR, and the root mean square of successive differences (RMSSD) to describe HRV were collected. PT males exhibited a tendency toward lower RMSSD (71.8 ± 22.6) compared to FT males (95.63 ± 29.0; p = 0.10). Female participants had a similar mean RMSSD in the FT and PT groups at 72.04 ± 33.2 and 74.0 ± 35.0, respectively. Serum 25-hydroxyvitamin D concentration did not correlate with cardiac autonomic function parameters. When assessing the lowest resting nighttime HRs and HRVs in a long-term, real-world context, healthy female PT young adults performed similarly to their FT peers. In contrast, the present study's results suggest that male PT young adults exhibit impaired autonomic cardiac function, potentially putting them at risk for cardiovascular disease later in adulthood.

Taste the emotions: pilot for a novel, sensors-based approach to emotional analysis during coffee tasting

BACKGROUND

Coffee is a natural drink with important properties for the human body and mind, capable of delivering energy and strong emotions, thus being appreciated since ancient times. The qualitative and quantitative assessment of the coffee properties is normally performed by trained panelists, though relying on standardized questionnaires, with possible biases arising. In this study, for the first time in the scientific literature, we applied a technology-based approach, based on the use of wearable sensors, to study the implicit emotional responses of a small cohort of experienced coffee judges, thus taking this chance to assess the feasibility of this approach in such a scenario. The merging of different technologies for capturing biomedical signals, including electrocardiogram, galvanic skin response, and electroencephalogram, was therefore adopted to retrieve results in terms of the relationships between implicit (i.e. psychophysiological) and explicit (i.e. derived from questionnaires) measurements.

RESULTS

Significant correlations were obtained between biomedical signals and data from the questionnaires within all the sensory domains (olfaction, vision, taste) investigated, particularly concerning autonomic-related features.

CONCLUSIONS

The results obtained confirmed the viability of this new approach in the psychophysical and emotional assessment in coffee tasting judges, paving the way for a new perspective into the universe of coffee quality assessment panels, eventually transferable to broader scale investigations, somewhat dealing with consumer satisfaction and neuromarketing at large. © 2023 Society of Chemical Industry.

Inhibitory Neurons in Nucleus Tractus Solitarius Are Involved in Decrease of Heart Rate Variability and Development of Depression-Like Behaviors in Temporal Lobe Epilepsy

BACKGROUND

Diminished heart rate variability (HRV) has been observed in epilepsy, especially in epilepsy with depressive disorders. However, the underlying mechanism remains elusive.

METHODS

We studied HRV, spontaneous recurrent seizures, and depression-like behaviors in different phases of pilocarpine-induced temporal lobe epilepsy (TLE) in mice. Single-cell RNA sequencing analysis was used to identify various nerve cell subsets in TLE mice with and without depression. Differentially expressed gene (DEG) analysis was performed in epilepsy, depression, and HRV central control-related brain areas.

RESULTS

We found decreased HRV parameters in TLE mice, and alterations were positively correlated with the severity of depression-like behaviors. The severity of depression-like behaviors was correlated with the frequency of spontaneous recurrent seizure. Characteristic expression of mitochondria-related genes was significantly elevated in mice with depression in glial cells, and the enrichment analysis of those DEGs showed an enriched GABAergic synapse pathway in the HRV central control-related brain area. Furthermore, inhibitory neurons in the nucleus tractus solitarius, which is an HRV central control-related brain area, were specifically expressed in TLE mice combined with depression compared with those in mice without depression. A significantly enriched long-term depression pathway in DEGs from inhibitory neurons was found.

CONCLUSIONS

Our study reported correlations between HRV and epilepsy-depression comorbidity in different phases of TLE. More importantly, we found that HRV central control-related inhibitory neurons are involved in the development of depression in TLE, providing new insights into epilepsy comorbid with depression.

Comprehensive evaluation of machine learning algorithms for predicting sleep-wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate variability

Introduction

Perinatal women tend to have difficulties with sleep along with autonomic characteristics. This study aimed to identify a machine learning algorithm capable of achieving high accuracy in predicting sleep-wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate variability (HRV).

Methods

Nine HRV indicators (features) and sleep-wake conditions of 154 pregnant women were measured for 1 week, from the 23rd to the 32nd weeks of pregnancy. Ten machine learning and three deep learning methods were applied to predict three types of sleep-wake conditions (wake, shallow sleep, and deep sleep). In addition, the prediction of four conditions, in which the wake conditions before and after sleep were differentiated-shallow sleep, deep sleep, and the two types of wake conditions-was also tested.

Results and Discussion

In the test for predicting three types of sleep-wake conditions, most of the algorithms, except for Naïve Bayes, showed higher areas under the curve (AUCs; 0.82-0.88) and accuracy (0.78-0.81). The test using four types of sleep-wake conditions with differentiation between the wake conditions before and after sleep also resulted in successful prediction by the gated recurrent unit with the highest AUC (0.86) and accuracy (0.79). Among the nine features, seven made major contributions to predicting sleep-wake conditions. Among the seven features, "the number of interval differences of successive RR intervals greater than 50 ms (NN50)" and "the proportion dividing NN50 by the total number of RR intervals (pNN50)" were useful to predict sleep-wake conditions unique to pregnancy. These findings suggest alterations in the vagal tone system specific to pregnancy.

Individualized Endurance Training Based on Recovery and Training Status in Recreational Runners

PURPOSE

Long-term development of endurance performance requires a proper balance between strain and recovery. Because responses and adaptations to training are highly individual, this study examined whether individually adjusted endurance training based on recovery and training status would lead to greater adaptations compared with a predefined program.

METHODS

Recreational runners were divided into predefined (PD; n = 14) or individualized (IND; n = 16) training groups. In IND, the training load was decreased, maintained, or increased twice a week based on nocturnal heart rate variability, perceived recovery, and heart rate-running speed index. Both groups performed 3-wk preparatory, 6-wk volume, and 6-wk interval periods. Incremental treadmill tests and 10-km running tests were performed before the preparatory period ( T0 ) and after the preparatory ( T1 ), volume ( T2 ), and interval ( T3 ) periods. The magnitude of training adaptations was defined based on the coefficient of variation between T0 and T1 tests (high >2×, low <0.5×).

RESULTS

Both groups improved ( P < 0.01) their maximal treadmill speed and 10-km time from T1 to T3 . The change in the 10-km time was greater in IND compared with PD (-6.2% ± 2.8% vs -2.9% ± 2.4%, P = 0.002). In addition, IND had more high responders (50% vs 29%) and fewer low responders (0% vs 21%) compared with PD in the change of maximal treadmill speed and 10-km performance (81% vs 23% and 13% vs 23%), respectively.

CONCLUSIONS

PD and IND induced positive training adaptations, but the individualized training seemed more beneficial in endurance performance. Moreover, IND increased the likelihood of high response and decreased the occurrence of low response to endurance training.

Conflict at Work Impairs Physiological Recovery during Sleep: A Daily Diary Study

Sleep plays an essential role in maintaining employees' health and well-being. However, stressors, such as conflict at work, may interfere with employees' sleep. Drawing on previous literature on the relationship between conflict at work and sleep outcomes, we proposed a negative relationship between daily conflict at work and physiological changes during early sleep, particularly nocturnal heart rate variability (HRV). Furthermore, building on the perseverative cognition hypothesis, we proposed that daily work-related rumination mediates the relationship between conflict at work and nocturnal HRV. Ninety-three healthcare employees participated in a daily diary study for five workdays, resulting in 419 observations. Multilevel analysis revealed a significant relationship between daily conflict at work and nocturnal HRV, specifically high-frequency (HF) power. Daily conflict at work was found to predict rumination; however, rumination did not significantly predict nocturnal HRV. Our results suggest that daily conflict at work increases rumination during the off-job time and may directly alter nocturnal HRV, specifically parasympathetic function in early sleep.

Reliability and Sensitivity of Nocturnal Heart Rate and Heart-Rate Variability in Monitoring Individual Responses to Training Load

PURPOSE

To assess the reliability of nocturnal heart rate (HR) and HR variability (HRV) and to analyze the sensitivity of these markers to maximal endurance exercise.

METHODS

Recreational runners recorded nocturnal HR and HRV on nights after 2 identical low-intensity training sessions (n = 15) and on nights before and after a 3000-m running test (n = 23). Average HR, the natural logarithm of the root mean square of successive differences (LnRMSSD), and the natural logarithm of the high-frequency power (LnHF) were analyzed from a full night (FULL), a 4-hour (4H) segment starting 30 minutes after going to sleep, and morning value (MOR) based on the endpoint of the linear fit through all 5-minute averages during the night. Differences between the nights were analyzed with a general linear model, and intraclass correlation coefficient (ICC) was used for internight reliability assessments.

RESULTS

All indices were similar between the nights followed by low-intensity training sessions. A very high ICC (P < .001) was observed in all analysis segments with a range of .97 to .98 for HR, .92 to .97 for LnRMSSD, and .91 to .96 for LnHF. HR increased (P < .001), whereas LnRMSSD (P < .01) and LnHF (P < .05) decreased after the 3000-m test compared with previous night only in 4H and FULL. Increments in HR (P < .01) and decrements in LnRMSSD (P < .05) were greater in 4H compared with FULL and MOR.

CONCLUSIONS

Nocturnal HR and HRV indices are highly reliable. Demanding maximal exercise increases HR and decreases HRV most systematically in 4H and FULL segments.

Hypoxia Differentially Affects Healthy Men and Women During a Daytime Nap With a Dose-Response Relationship: a Randomized, Cross-Over Pilot Study

Context: The use of daytime napping as a countermeasure in sleep disturbances has been recommended but its physiological evaluation at high altitude is limited. Objective: To evaluate the neuroendocrine response to hypoxic stress during a daytime nap and its cognitive impact. Design, Subject, and Setting: Randomized, single-blind, three period cross-over pilot study conducted with 15 healthy lowlander subjects (8 women) with a mean (SD) age of 29(6) years (Clinicaltrials identifier: NCT04146857, https://clinicaltrials.gov/ct2/show/NCT04146857?cond=napping&draw=3&rank=12). Interventions: Volunteers underwent a polysomnography, hematological and cognitive evaluation around a 90 min midday nap, being allocated to a randomized sequence of three conditions: normobaric normoxia (NN), normobaric hypoxia at FiO2 14.7% (NH15) and 12.5% (NH13), with a washout period of 1 week between conditions. Results: Primary outcome was the interbeat period measured by the RR interval with electrocardiogram. Compared to normobaric normoxia, RR during napping was shortened by 57 and 206 ms under NH15 and NH13 conditions, respectively (p < 0.001). Sympathetic predominance was evident by heart rate variability analysis and increased epinephrine levels. Concomitantly, there were significant changes in endocrine parameters such as erythropoietin (∼6 UI/L) and cortisol (∼100 nmol/L) (NH13 vs. NN, p < 0.001). Cognitive evaluation revealed changes in the color-word Stroop test. Additionally, although sleep efficiency was preserved, polysomnography showed lesser deep sleep and REM sleep, and periodic breathing, predominantly in men. Conclusion: Although napping in simulated altitude does not appear to significantly affect cognitive performance, sex-dependent changes in cardiac autonomic modulation and respiratory pattern should be considered before napping is prescribed as a countermeasure.

Interictal Heart Rate Variability as a Biomarker for Comorbid Depressive Disorders among People with Epilepsy

Depressive disorders are common among people with epilepsy (PwE). We here aimed to report an unbiased automatic classification of epilepsy comorbid depressive disorder cases via training a linear support vector machine (SVM) model using the interictal heart rate variability (HRV) data. One hundred and eighty-six subjects participated in this study. Among all participants, we recorded demographic information, epilepsy states and neuropsychiatric features. For each subject, we performed simultaneous electrocardiography and electroencephalography recordings both in wakefulness and non-rapid eye movement (NREM) sleep stage. Using these data, we systematically explored the full parameter space in order to determine the most effective combinations of data to classify the depression status in PwE. PwE with depressive disorders exhibited significant alterations in HRV parameters, including decreased time domain and nonlinear domain values both in wakefulness and NREM sleep stage compared with without depressive disorders and non-epilepsy controls. Interestingly, PwE without depressive disorder showed the same level of HRV values as the non-epilepsy control subjects. The SVM classification model of PwE depression status achieved a higher classification accuracy with the combination of HRV parameters in wakefulness and NREM sleep stage. Furthermore, the receiver operating characteristic (ROC) curve of the SVM classification model showed a satisfying area under the ROC curve (AUC: 0.758). Intriguingly, we found that the HRV measurements during NREM sleep are particularly important for correct classification, suggesting a mechanistic link between the dysregulation of heart rate during sleep and the development of depressive disorders in PwE. Our classification model may provide an objective measurement to assess the depressive status in PwE.

Reliability of Heart Rate Variability During Stable and Disrupted Polysomnographic Sleep

Heart rate variability (HRV) is commonly used within sleep and cardiovascular research, yet HRV reliability across various sleep stages remains equivocal. The present study examined the reliability of frequency- and time-domain HRV within stage II (N2), slow wave (SWS), and rapid eye movement (REM) sleep during both stable and disrupted sleep. We hypothesized that high-frequency (HF) HRV would be reliable in all three sleep stages, low-frequency (LF) HRV would be reliable during N2 and SWS, and that disrupted sleep via spontaneous cortical arousals would decrease HRV reliability. Twenty-seven participants (11 male, 16 female, 26±1 years) were equipped with laboratory polysomnography for one night. Both frequency- and time-domain HRV were analyzed in two 5-10 minute blocks during multiple stable and disrupted sleep cycles across N2, SWS and REM sleep. HF HRV was highly correlated across stable N2 (r=0.839, p<0.001), SWS (r=0.765, p<0.001) and REM (r=0.881, p<0.001). LF HRV was moderate-to-highly correlated during stable cycles of N2 sleep (r=0.694, p < 0.001), SWS, (r=0.765, p < 0.001), and REM (r=0.699, p<0.001) sleep. When stable sleep was compared with disrupted sleep, both time- and frequency-domain HRV were reliable (α>0.90, p<0.05) in N2, SWS, and REM, with the exception of LF HRV during SWS (α=0.62, p=0.089). In conclusion, time- and frequency-domain HRV demonstrated reliability across stable N2, SWS and REM sleep, and remained reliable during disrupted sleep. These findings support the use of HRV during sleep as a tool for assessing cardiovascular health and risk stratification.

Sympathovagal Balance Is a Strong Predictor of Post High-Volume Endurance Exercise Cardiac Arrhythmia

Regular physical activity is important for cardiovascular health. However, high-volume endurance exercise has been associated with increased number of electrocardiogram (ECG) abnormalities, including disturbances in cardiac rhythm (arrhythmias) and abnormalities in ECG pattern. The aim of this study was to assess if heart rate variability (HRV) is associated with ECG abnormalities. Fifteen participants with previous cycling experience completed a 21-day high-volume endurance exercise cycle over 3,515 km. Participants wore a 5-lead Holter monitor for 24 h pre- and post-exercise, which was used to quantify ECG abnormalities and export sinus R-to-R intervals (NN) used to calculate HRV characteristics. As noise is prevalent in 24-h HRV recordings, both 24-h and heart rate collected during stable periods of time (i.e., deep sleep) were examined. Participants experienced significantly more arrhythmias post high-volume endurance exercise (median = 35) compared to pre (median = 12; p = 0.041). All 24-h and deep sleep HRV outcomes were not different pre-to-post high-volume endurance exercise (p &gt; 0.05). Strong and significant associations with arrhythmia number post-exercise were found for total arrhythmia (total arrhythmia number pre-exercise, ρ = 0.79; age, ρ = 0.73), supraventricular arrhythmia (supraventricular arrhythmia number pre-exercise: ρ = 0.74; age: ρ = 0.66), and ventricular arrhythmia (age: ρ = 0.54). As a result, age and arrhythmia number pre-exercise were controlled for in hierarchical regression, which revealed that only deep sleep derived low frequency to high frequency (LF/HF) ratio post high-volume endurance exercise predicted post total arrhythmia number (B = 0.63, R2Δ = 34%, p = 0.013) and supraventricular arrhythmia number (B = 0.77, R2Δ = 69%, p &lt; 0.001). In this study of recreationally active people, only deep sleep derived LF/HF ratio was associated with more total and supraventricular arrhythmias after high-volume endurance exercise. This finding suggests that measurement of sympathovagal balance during deep sleep might be useful to monitor arrhythmia risk after prolonged high-volume endurance exercise performance.

Rhythmicity in heart rate and its surges usher a special period of sleep, a likely home for PGO waves

High amplitude electroencephalogram (EEG) events, like unitary K-complex (KC), are used to partition sleep into stages and hence define the hypnogram, a key instrument of sleep medicine. Throughout sleep the heart rate (HR) changes, often as a steady HR increase leading to a peak, what is known as a heart rate surge (HRS). The hypnogram is often unavailable when most needed, when sleep is disturbed and the graphoelements lose their identity. The hypnogram is also difficult to define during normal sleep, particularly at the start of sleep and the periods that precede and follow rapid eye movement (REM) sleep. Here, we use objective quantitative criteria that group together periods that cannot be assigned to a conventional sleep stage into what we call REM0 periods, with the presence of a HRS one of their defining properties. Extended REM0 periods are characterized by highly regular sequences of HRS that generate an infra-low oscillation around 0.05 Hz. During these regular sequence of HRS, and just before each HRS event, we find avalanches of high amplitude events for each one of the mass electrophysiological signals, i.e. related to eye movement, the motor system and the general neural activity. The most prominent features of long REM0 periods are sequences of three to five KCs which we label multiple K-complexes (KCm). Regarding HRS, a clear dissociation is demonstrated between the presence or absence of high gamma band spectral power (55-95 Hz) of the two types of KCm events: KCm events with strong high frequencies (KCmWSHF) cluster just before the peak of HRS, while KCm between HRS show no increase in high gamma band (KCmNOHF). Tomographic estimates of activity from magnetoencephalography (MEG) in pre-KC periods (single and multiple) showed common increases in the cholinergic Nucleus Basalis of Meynert in the alpha band. The direct contrast of KCmWSHF with KCmNOHF showed increases in all subjects in the high sigma band in the base of the pons and in three subjects in both the delta and high gamma bands in the medial Pontine Reticular Formation (mPRF), the putative Long Lead Initial pulse (LLIP) for Ponto-Geniculo-Occipital (PGO) waves.

Association between nocturnal heart rate variability and incident cardiovascular disease events: The HypnoLaus population-based study

BACKGROUND

Although heart rate variability (HRV) is widely used to assess cardiac autonomic function, few studies have specifically investigated nocturnal HRV.

OBJECTIVE

The purpose of this study was to assess the association between nocturnal HRV and cardiovascular disease (CVD) incidence over 4 years in a population-based sample.

METHODS

A total of 1784 participants (48.2% men; 58 ± 11 years) from the HypnoLaus population-based cohort free of CVD at baseline were included. Polysomnography-based electrocardiograms were exported to analyze time- and frequency-domain HRV, Poincaré plots indices, detrended fluctuation analysis, acceleration capacity (AC) and deceleration capacity (DC), entropy, heart rate fragmentation (HRF), and heart rate turbulence. Multivariable-adjusted Cox regression analysis was used to assess the association between HRV indices and incident CVD events.

RESULTS

Sixty-seven participants (3.8%) developed CVD over mean follow-up of 4.1 ± 1.1 years. In a fully adjusted model, AC (hazard ratio per 1-SD increase; 95% confidence interval: 1.59; 1.17-2.16; P = .004), DC (0.63; 0.47-0.84; P = .002), and HRF (1.41; 1.11-1.78; P = .005) were the only HRV metrics significantly associated with incident CVD events after controlling for false discovery rate.

CONCLUSION

Nocturnal novel HRV parameters such as AC, DC, and HRF are better predictors of CVD events than time and frequency traditional HRV parameters. These findings suggest a form of dysautonomia and fragmented rhythms, but further experimental studies are needed to delineate the underlying physiological mechanisms of these novel HRV parameters.

An artificial neural network for automated behavioral state classification in rats

Accurate behavioral state classification is critical for many research applications. Researchers typically rely upon manual identification of behavioral state through visual inspection of electrophysiological signals, but this approach is time intensive and subject to low inter-rater reliability. To overcome these limitations, a diverse set of algorithmic approaches have been put forth to automate the classification process. Recently, novel machine learning approaches have been detailed that produce rapid and highly accurate classifications. These approaches however, are often computationally expensive, require significant expertise to implement, and/or require proprietary software that limits broader adoption. Here we detail a novel artificial neural network that uses electrophysiological features to automatically classify behavioral state in rats with high accuracy, sensitivity, and specificity. Common parameters of interest to sleep scientists, including state-dependent power spectra and homeostatic non-REM slow wave activity, did not significantly differ when using this automated classifier as compared to manual scoring. Flexible options enable researchers to further increase classification accuracy through manual rescoring of a small subset of time intervals with low model prediction certainty or further decrease researcher time by generalizing trained networks across multiple recording days. The algorithm is fully open-source and coded within a popular, and freely available, software platform to increase access to this research tool and provide additional flexibility for future researchers. In sum, we have developed a readily implementable, efficient, and effective approach for automated behavioral state classification in rats.

Physiologic Response to the Pfizer-BioNTech COVID-19 Vaccine Measured Using Wearable Devices: Prospective Observational Study

Background

The Pfizer-BioNTech COVID-19 vaccine uses a novel messenger RNA technology to elicit a protective immune response. Short-term physiologic responses to the vaccine have not been studied using wearable devices.

Objective

We aim to characterize physiologic changes in response to COVID-19 vaccination in a small cohort of participants using a wearable device (WHOOP Strap 3.0). This is a proof of concept for using consumer-grade wearable devices to monitor response to COVID-19 vaccines.

Methods

In this prospective observational study, physiologic data from 19 internal medicine residents at a single institution that received both doses of the Pfizer-BioNTech COVID-19 vaccine was collected using the WHOOP Strap 3.0. The primary outcomes were percent change from baseline in heart rate variability (HRV), resting heart rate (RHR), and respiratory rate (RR). Secondary outcomes were percent change from baseline in total, rapid eye movement, and deep sleep. Exploratory outcomes included local and systemic reactogenicity following each dose and prophylactic analgesic use.

Results

In 19 individuals (mean age 28.8, SD 2.2 years; n=10, 53% female), HRV was decreased on day 1 following administration of the first vaccine dose (mean –13.44%, SD 13.62%) and second vaccine dose (mean –9.25%, SD 22.6%). RHR and RR showed no change from baseline after either vaccine dose. Sleep duration was increased up to 4 days post vaccination, after an initial decrease on day 1. Increased sleep duration prior to vaccination was associated with a greater change in HRV. Local and systemic reactogenicity was more severe after dose two.

Conclusions

This is the first observational study of the physiologic response to any of the novel COVID-19 vaccines as measured using wearable devices. Using this relatively small healthy cohort, we provide evidence that HRV decreases in response to both vaccine doses, with no significant changes in RHR or RR. Sleep duration initially decreased following each dose with a subsequent increase thereafter. Future studies with a larger sample size and comparison to other inflammatory and immune biomarkers such as antibody response will be needed to determine the true utility of this type of continuous wearable monitoring in regards to vaccine responses. Our data raises the possibility that increased sleep prior to vaccination may impact physiologic responses and may be a modifiable way to increase vaccine response. These results may inform future studies using wearables for monitoring vaccine responses.

Trial Registration

ClinicalTrials.gov NCT04304703; https://www.clinicaltrials.gov/ct2/show/NCT04304703

Heart rate variability during sleep in children and adolescents with restless sleep disorder: a comparison with restless legs syndrome and normal controls

STUDY OBJECTIVES

Restless sleep disorder (RSD) has recently been characterized clinically and polysomnographically in children and differentiated from restless legs syndrome (RLS). Heart rate variability is a reliable method to quantify autonomic changes during sleep. The aim of this study was to characterize heart rate variability in children with RSD, RLS, and individuals without these disorders, with the hypothesis that children with RSD have a shift toward sympathetic predominance during sleep.

METHODS

We analyzed polysomnographic recordings from 32 children who fulfilled RSD diagnostic criteria (19 boys and 13 girls), 32 children with RLS (20 boys and 12 girls), and 33 individuals without disorders (17 boys and 16 girls). Four electrocardiographic epochs were chosen, 1 for each stage, and were analyzed for automatic detection of R waves. Time domain and frequency domain heart rate variability parameters were obtained and analyzed.

RESULTS

In terms of time domain, only the standard deviation of the average interval between successive R waves during stage N3 was slightly but significantly higher in patients with RSD than in patients with RLS. In terms of frequency domain, in patients with RSD, the very-low-frequency and low-frequency bands were increased (vs patients with RLS and individuals without disorders, respectively), whereas low-frequency/high-frequency ratio tended to be increased in both patients with RSD and with RLS. In rapid eye movement sleep, low-frequency/high-frequency ratio was increased in both patients with RSD and with RLS. The low-frequency/high-frequency ratio increased in patients with RLS during quiet wakefulness preceding sleep.

CONCLUSIONS

Children with RSD have increased sympathetic activation during sleep, particularly N3 and rapid eye movement sleep, compared with individuals without disorders but, as expected, not during wakefulness. Differently, children with RLS have sympathetic activation during relaxed wakefulness preceding sleep and during sleep.

Impact of Water Temperature on Heart Rate Variability during Bathing

Background: Heart rate variability (HRV) is affected by many factors. This paper aims to explore the impact of water temperature (WT) on HRV during bathing. Methods: The bathtub WT was preset at three conditions: i.e., low WT (36–38 °C), medium WT (38–40 °C), and high WT (40–42 °C), respectively. Ten subjects participated in the data collection. Each subject collected five electrocardiogram (ECG) recordings at each preset bathtub WT condition. Each recording was 18 min long with a sampling rate of 200 Hz. In total, 150 ECG recordings and 150 WT recordings were collected. Twenty HRV features were calculated using 1-min ECG segments each time. The k-means clustering analysis method was used to analyze the rough trends based on the preset WT. Analyses of the significant differences were performed using the multivariate analysis of variance of t-tests, and the mean and standard deviation (SD) of each HRV feature based on the WT were calculated. Results: The statistics show that with increasing WT, 11 HRV features are significantly (p < 0.05) and monotonously reduced, four HRV features are significantly (p < 0.05) and monotonously rising, two HRV features are rising first and then reduced, two HRV features (fuzzy and approximate entropy) are almost unchanged, and vLF power is rising. Conclusion: The WT has an important impact on HRV during bathing. The findings in the present work reveal an important physiological factor that affects the dynamic changes of HRV and contribute to better quantitative analyses of HRV in future research works.

Heart Rate Variability and Firstbeat Method for Detecting Sleep Stages in Healthy Young Adults: Feasibility Study

Background

Polysomnography (PSG) is considered the only reliable way to distinguish between different sleep stages. Wearable devices provide objective markers of sleep; however, these devices often rely only on accelerometer data, which do not enable reliable sleep stage detection. The alteration between sleep stages correlates with changes in physiological measures such as heart rate variability (HRV). Utilizing HRV measures may thus increase accuracy in wearable algorithms.

Objective

We examined the validity of the Firstbeat sleep analysis method, which is based on HRV and accelerometer measurements. The Firstbeat method was compared against PSG in a sample of healthy adults. Our aim was to evaluate how well Firstbeat distinguishes sleep stages, and which stages are most accurately detected with this method.

Methods

Twenty healthy adults (mean age 24.5 years, SD 3.5, range 20-37 years; 50% women) wore a Firstbeat Bodyguard 2 measurement device and a Geneactiv actigraph, along with taking ambulatory SomnoMedics PSG measurements for two consecutive nights, resulting in 40 nights of sleep comparisons. We compared the measures of sleep onset, wake, combined stage 1 and stage 2 (light sleep), stage 3 (slow wave sleep), and rapid eye movement (REM) sleep between Firstbeat and PSG. We calculated the sensitivity, specificity, and accuracy from the 30-second epoch-by-epoch data.

Results

In detecting wake, Firstbeat yielded good specificity (0.77), and excellent sensitivity (0.95) and accuracy (0.93) against PSG. Light sleep was detected with 0.69 specificity, 0.67 sensitivity, and 0.69 accuracy. Slow wave sleep was detected with 0.91 specificity, 0.72 sensitivity, and 0.87 accuracy. REM sleep was detected with 0.92 specificity, 0.60 sensitivity, and 0.84 accuracy. There were two measures that differed significantly between Firstbeat and PSG: Firstbeat underestimated REM sleep (mean 18 minutes, P=.03) and overestimated wake time (mean 14 minutes, P<.001).

Conclusions

This study supports utilizing HRV alongside an accelerometer as a means for distinguishing sleep from wake and for identifying sleep stages. The Firstbeat method was able to detect light sleep and slow wave sleep with no statistically significant difference to PSG. Firstbeat underestimated REM sleep and overestimated wake time. This study suggests that Firstbeat is a feasible method with sufficient validity to measure nocturnal sleep stage variation.

Wearable Sensors for Assessing the Role of Olfactory Training on the Autonomic Response to Olfactory Stimulation

Wearable sensors are nowadays largely employed to assess physiological signals derived from the human body without representing a burden in terms of obtrusiveness. One of the most intriguing fields of application for such systems include the assessment of physiological responses to sensory stimuli. In this specific regard, it is not yet known which are the main psychophysiological drivers of olfactory-related pleasantness, as the current literature has demonstrated the relationship between odor familiarity and odor valence, but has not clarified the consequentiality between the two domains. Here, we enrolled a group of university students to whom olfactory training lasting 3 months was administered. Thanks to the analysis of electrocardiogram (ECG) and galvanic skin response (GSR) signals at the beginning and at the end of the training period, we observed different autonomic responses, with higher parasympathetically-mediated response at the end of the period with respect to the first evaluation. This possibly suggests that an increased familiarity to the proposed stimuli would lead to a higher tendency towards relaxation. Such results could suggest potential applications to other domains, including personalized treatments based on odors and foods in neuropsychiatric and eating disorders.

Relationship of Cardiac Autonomic Modulation with Cardiovascular Parameters in Adults, According to Body Mass Index and Physical Activity

This study aimed to analyze the relationship between cardiac autonomic modulation (CAM) and cardiovascular parameters (blood pressure and resting heart rate) in a sample of 256 adults, grouped by body mass index and sufficient moderate-to-vigorous physical activity (≥150 min/week). The sample showed different cardiovascular parameters and CAM according to body mass index, but not according to physical activity. Adults who are overweight and physically active presented higher relationship between CAM and blood pressure than those who are insufficiently active, similarly to normal weight groups. Recommended levels of physical activity may play an important role in the relationship of HRV with cardiovascular parameters in overweight adults, regardless of sex, age, socioeconomic level, and central fat. Trial registration: Registered at ClinicalTrials.gov (NCT03986879). Graphical abstract.

Sleep assessment by means of a wrist actigraphy-based algorithm: agreement with polysomnography in an ambulatory study on older adults

The purpose of the present work is to examine, on a clinically diverse population of older adults (N = 46) sleeping at home, the performance of two actigraphy-based sleep tracking algorithms (i.e., Actigraphy-based Sleep algorithm, ACT-S1 and Sadeh's algorithm) compared to manually scored electroencephalography-based PSG (PSG-EEG). ACT-S1 allows for a fully automatic identification of sleep period time (SPT) and within the identified sleep period, the sleep-wake classification. SPT detected by ACT-S1 did not differ statistically from using PSG-EEG (bias = -9.98 min; correlation 0.89). In sleep-wake classification on 30-s epochs within the identified sleep period, the new ACT-S1 presented similar or slightly higher accuracy (83-87%), precision (86-89%) and F1 score (90-92%), significantly higher specificity (39-40%), and significantly lower, but still high, sensitivity (96-97%) compared to Sadeh's algorithm, which achieved 99% sensitivity as the only measure better than ACT-S1's. Total sleep times (TST) estimated with ACT-S1 and Sadeh's algorithm were higher, but still highly correlated to PSG-EEG's TST. Sleep quality metrics of sleep period efficiency and wake-after-sleep-onset computed by ACT-S1 were not significantly different from PSG-EEG, while the same sleep quality metrics derived by Sadeh's algorithm differed significantly from PSG-EEG. Agreement between ACT-S1 and PSG-EEG reached was highest when analyzing the subset of subjects with least disrupted sleep (N = 28). These results provide evidence of promising performance of a full-automation of the sleep tracking procedure with ACT-S1 on older adults. Future longitudinal validations across specific medical conditions are needed. The algorithm's performance may further improve with integrating multi-sensor information.

Lying Awake at Night: Cardiac Autonomic Activity in Relation to Sleep Onset and Maintenance

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 participants during a single night. Cardiac autonomic activity was assessed using frequency domain analysis of RR intervals and results show that the normalized spectral power in the low frequency band (LF_nu) after sleep onset was significantly higher in participants with long SOL compared to participants with short SOL. Furthermore, the normalized spectral power in the high frequency band (HF_nu) was significantly lower in participants with long SOL as compared to participants with short SOL over 3 time periods (first 10 min in bed intending to sleep, 10 min before, and 10 min after sleep onset). These results suggest that participants with long SOL are more aroused in all three examined time periods when compared to participants with short SOL, especially for young adults (20–40 years). As there is no clear consensus on the cutoff for an increased WASO, we used a data-driven approach to explore different cutoffs to define short WASO and long WASO groups. LF_nu, HF_nu, and LF/HF differed between the long and the short WASO groups. A higher LF_nu and LF/HF and a lower HF_nu was observed in participants with long WASO for most cutoffs. The highest effect size was found using the cutoff of 66 min. Our findings suggest that autonomic cardiac activity has predictive value with respect to sleep characteristics pertaining to sleep onset and maintenance.

Posttraumatic stress disorder diagnosis is associated with reduced parasympathetic activity during sleep in US veterans and military service members of the Iraq and Afghanistan wars

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 self-report measures of sleep quality, insomnia severity, and disruptive nocturnal behaviors. Participants then completed a laboratory-based polysomnographic study night with concurrent HRV assessment.

Results

Participants with PTSD (N = 29) had lower HF-HRV in overall NREM sleep relative to those without PTSD (N = 33) (F(1, 54) = 4.24, p = .04). Groups did not differ on overall HF-HRV during REM sleep. HF-HRV increased over the night for the sample as a whole during both NREM and REM sleep. PTSD status did not moderate the association between HF-HRV and sleep cycles. However, the PTSD group had lower HF-HRV in the first t(155) = 2.67, p = .008, and fourth NREM cycles, t(155) = 2.11, p = .036, relative to participants without PTSD.

Conclusions

Findings suggest blunted parasympathetic modulation during NREM sleep in a young cohort of military veterans and service-members with PTSD. Findings are concerning considering the increased risk of incident cardiovascular events associated with impaired parasympathetic nervous system function. Reduced parasympathetic modulation may be one mechanism underlying the increased prevalence of cardiovascular disease (CVD) among veterans with PTSD.

Increased Activity in Patients with Cardiovascular Risk Factors Increases Heart Rate Variability

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 stable angina pectoris. Physical activity and HF were measured using activity monitors and 24-hour Holter monitors at baseline and 6 months later. The physical activity increased in 28 patients (increase group) and decreased in 20 patients (decrease group) after 6 months. In this study, after 6 months, compared to the decreased physical activity group, the increased physical activity group showed a significant increase in the HF index during the first hour after sleep onset. Therefore, the increase in the HF index may have been due to the increase in physical activity. An increase in physical activity suggests that the quality of sleep early in the sleep cycle may be improved, which may affect the patient's prognosis.

Sleep quality prediction in caregivers using physiological signals

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, which is expensive and potentially disrupts the caregiving routine. To address these issues, we propose a clinical decision support system to predict sleep quality based on trends of physiological signals in the deep sleep stage. This system utilizes four raw physiological signals using a wearable device (E4 wristband): heart rate variability, electrodermal activity, body movement, and skin temperature. To evaluate the performance of the proposed method, analyses were conducted on a two-week period of sleep monitored on eight CPWD. The best performance is achieved using the random forest classifier with an accuracy of 75% for sleep quality, and 73% for restfulness, respectively. We found that the most important features to detect these measures are sleep efficiency (ratio of amount of time asleep to the amount of time in bed) and skin temperature. The results from our sleep analysis system demonstrate the capability of using wearable sensors to measure sleep quality and restfulness in CPWD.

Emotional response to perceived racism and nocturnal heart rate variability in young adult African Americans

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 consequences in African Americans. Perceived racism has been linked to ANS activity, however, we are not aware of prior research on racism and nocturnal ANS balance.

OBJECTIVE

To examine relationships between perceived racism and nocturnal ANS activity indexed by heart rate variability (HRV) in healthy African American men and women age 18-35.

METHODS

Fifty-four participants completed the Perceived Racism Scale and had 24-hour ambulatory electrocardiogram recordings in their homes. Power spectral analysis was used to derive normalized high frequency (nHF) to index PNS activity which was computed by 5-minute epochs during wake and sleep.

RESULTS

Endorsement of racism and negative emotional reactions during the past year were inversely related to nHF during time in bed. Multiple regression analysis indicated that negative emotional reactions were a significant predictor of nHF during the sleep period F(2,54) = 4.213, p = .020, R² = 0.135 (adjusted R² = 0.103). Relationships during wake were not statistically significant.

CONCLUSION

Findings suggest that perseverative thoughts triggered by negative emotional reactions to racism influencing nocturnal ANS activity may be a pathway by which perceived racism affects health. Support: 3UL1TR001409-02S1 and R01HL087995 to Dr. Mellman.

The effects of a 120-minute nap on sleepiness, fatigue, and performance during 16-hour night shifts: A pilot study

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 and fatigue, a single‐digit mental arithmetic task (for 10 minutes), and heart rate variability. Participants wore an ActiGraph to estimate their sleep state.

Results

There was no difference in the sleep parameters at the time of naps among the three conditions. Immediately following a 120‐minute nap, sleepiness and fatigue increased, and the number of calculations performed in the single‐digit mental arithmetic task decreased in any of the conditions. In particular, immediately after the 02‐NAP, fatigue and high‐frequency power (HF) were higher than after the 22‐NAP. In the early morning (from 05:00 to 09:00), in the 22‐NAP, sleepiness and fatigue increased, and performance and sublingual temperature decreased more than in the 00‐NAP and 02‐NAP. Furthermore, the ratio of errors was significantly lower in the 00‐NAP than in the 22‐NAP in the early morning.

Conclusions

A 120‐minute nap taken from 22:00 to 02:00 may cause temporary sleepiness after waking, increase fatigue and reduce performance. Greater attention should be given to naps taken at a later time (ie, 02‐NAP). In addition, taking a nap starting at 00:00 might decrease the risks of errors in the morning.

Transcranial Impedance Changes during Sleep: A Rheoencephalography Study

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 changes in cerebral blood flow (CBF) was confirmed by the analysis of the signal during breathing maneuvers with known effects on CBF. The mean amplitude and variability of the REG characteristic parameters were averaged across all participants and were compared between different stages of sleep.

RESULTS

Average transcranial impedance was significantly lower during non-REM stages N1 and N2, compared to other sleep stages, suggesting a decrease in CBF volume. Stage N3 showed the slowest frequency indicating a slow heart rate during this stage. N3 also had the lowest variability in frequency and peak-to-trough amplitude.

CONCLUSION

Measurement of transcranial electrical conductivity may be a viable non-invasive method for monitoring any potential changes in intracranial fluid homeostasis. Clinical Impact: In the absence of other convenient non-invasive methods, using REG to track intracranial fluid dynamics during sleep can facilitate an improved understanding of pathogenesis in Alzheimer's disease.

Influence of a 30-Day Slow-Paced Breathing Intervention Compared to Social Media Use on Subjective Sleep Quality and Cardiac Vagal Activity

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 randomly allocated to an experimental or control group. In the experimental group, they had to perform slow-paced breathing for 15 min each evening across a 30-day period. This was administered through a smartphone application. The control group used social media (e.g., Facebook, Instagram, Whatsapp) for the same duration. The night before and after the intervention, their CVA was assessed via a light portable Electrocardiogram (ECG) device, and they had to fill out the Pittsburgh Sleep Quality Index questionnaire. Results showed that in comparison to the use of social media, the slow-paced breathing technique improved subjective sleep quality and increased overnight CVA, while a tendency was observed for morning awakening CVA. Slow-paced breathing appears a promising cost-effective technique to improve subjective sleep quality and cardiovascular function during sleep in young healthy individuals.