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Background: Compared to day workers, shift workers face an elevated risk of cardiovascular disease. We reviewed the evidence to address the research question: Does acute exposure to shift work impact (blunt) the natural drop (dip) in Blood Pressure (BP) occurring during sleep and/or nighttime hours? (PROSPERO CRD42018110847). Methods: We performed a systematic review of five databases. We compared pooled estimates of mean BP stratified by periods of shift work, rest/leisure, and sleep, and evaluated the quality of evidence with the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework. Results: Our search covered 1/1/1980-10/24/2018 and yielded 1,636 records. Inter-rater agreement during screening was high (Kappa=0.87). We retained 44 studies described in 50 publications. We identified wide variation in shift worker type, shift schedules, and regularity of BP measurements. Most studies examined BP during one shift workday and one rest/leisure day. No study examined the impact of repeated exposure to shift work on the sleep-related dip in BP. Eighteen studies examined night shifts and one reported on BP during sleep post night shift. Compared to BP measured during shift work, BP measured during any sleep period separate from shift work was lower by 17.5 mmHg Systolic BP (95%CI 15.75, 19.27) and 15.4 mmHg lower for Diastolic BP (95%CI 14.38, 16.42) (p Conclusions: There is limited research exploring the acute and long-term impact of shift work on BP during sleep. The available evidence is heterogenous, low quality, and suggests that the mean dip in BP during sleep separate from shift work is not blunted.

The present study examined both between- and within-person effects of maternal sleep patterns on quality of mothering at bedtime during infants' first 6 months. Participants included 142 mothers who reported on their daily fall asleep and wake times across seven consecutive days with a daily sleep diary when infants were 1, 3, and 6 months old. At each age point, maternal emotional availability during one night of infant bedtime was observed and scored by trained observers who were blind to maternal sleep patterns. Multilevel modeling revealed that mothers with irregular sleep patterns, especially later average fall asleep times and greater average variability in sleep period across three age points, showed poorer parenting quality with infants at bedtime than other mothers. In addition, both between- and within-person effects of maternal sleep on bedtime parenting quality changed with infant age. Compared to mothers' individual averages across 1, 3, and 6 months, maternal short average sleep period, increased variability in sleep period, and later fall asleep times predicted poorer bedtime parenting quality at 6 months, but not at 1 or 3 months. Results emphasize the importance of maternal sleep regulation and sleep hygiene for maternal parenting quality, especially as infants get older. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Background and objective With the acceleration of social rhythm and the increase of pressure, there are various sleep problems among people. Sleep staging is an important basis for the diagnosis of sleep disorders and other related diseases. The process of automatic staging of sleep is mainly divided into three core steps: data preprocessing, feature extraction, and classification. Accurate analysis of the features of sleep electroencephalogram (EEG) signals is not only helpful to improve the accuracy of sleep staging, but also help people to understand their sleep status. Methods This paper focuses on the analysis of EEG features during sleep staging, and reviews many feature extraction methods and classification methods for sleep staging and sums up these algorithms used in literatures and its staging results. Besides, this paper lists a total of 22 features based on time domain, time-frequency, and nonlinear analysis methods, including kurtosis, skewness, Hjorth parameters, and standard deviations, wavelets energy; sample entropy (SampEn), fuzzy entropy, Tsallis entropy, fractal dimension (FD), complexity. The data set comes from EDF database. Wavelet transform (WT) and support vector machine (SVM) are used to achieve the sleep staging based on single-channel EEG signal. And the characteristic feature data was analyzed by ANOVA. Results By comparison, the SampEn, fuzzy entropy, FD and complexity can achieve ideal sleep staging. The highest accuracy of sleep staging is 85.93%. The FD and complexity are simpler than the entropy value, but their accuracies are lower. Furthermore, the distribution of these methods in different sleep period is more significant than others, which is content with the results of sleep staging. Conclusion In a word, due to the non-stationary and non-linear characteristics of EEG signals, time domain and time-frequency analysis methods all have some limitations. Nonlinear analysis was more effective and practical for the analysis of sleep EEG.

The around-the-clock smartphone use and its relation to disturbed sleep is a public health concern. The present study aimed to quantify the effects of different dimensions of smartphone behaviours (frequency of daytime use, problematic use, use before sleep and use during the sleep period) on disturbed sleep (sleep quality and sleep quantity) and to disentangle their inter-relationship in a large population-based sample of 24,856 Danish adults aged ≥16 years. Data come from the SmartSleep Experiment, which is a web-based survey carried out using a citizen science approach. Tested items were used to evaluate smartphone use and disturbed sleep was evaluated with the Karolinska Sleep Questionnaire (KSQ). Linear and multinomial logistic regression was employed to evaluate the relationship between smartphone use and disturbed sleep. While several of the smartphone measures were associated with disturbed sleep when assessed individually, smartphone use during the sleep period was the only dimension consistently associated with disturbed sleep when assessed independently of other smartphone behaviours. Weekly smartphone use during the sleep period versus no use was associated on average with a 0.96 point higher score (95% confidence interval [CI] 0.90-1.02) on the 5-point KSQ scale, and a higher risk of both short (odds ratio [OR] 1.32, 95% CI 1.08-1.62) and long (OR 1.94, 95% CI 1.63-2.32) sleep duration. Smartphone use during the sleep period is the factor strongest associated to disturbed sleep relative to other dimensions of smartphone use. Recommendations around smartphone use during the sleep period are warranted in order to protect the fundamentally important biological and mental processes of sleep.

Studies have yielded inconsistent evidence for an association between long-term average wind turbine sound pressure level (SPL) and disturbed sleep. Transient changes in sleep may be more susceptible to short-term variations in wind turbine SPL throughout the sleep period time. We analyzed sleep actigraphy data (participant sleep nights = 2,094, males = 151, females = 192) in 10 min intervals time-synchronized to wind turbine supervisory control and data acquisition. Calculated indoor wind turbine SPL was considered after adjusting for turbine rotor speed and closed/open bedroom windows. Maximum calculated nightly average wind turbine SPL reached 44.7 dBA (mean = 32.9, SD = 6.4) outdoors and 31.4 dBA (mean = 12.5, SD = 8.3) indoors. Wind turbine SPL in 10 min intervals, and nightly averages, was not statistically associated with actigraphy outcomes. However, the variability in wind turbine SPL due to changes in wind turbine operation across the sleep period time, as measured by the difference between the 10 min SPL and the nightly average SPL (∆SPL), was statistically related to awakenings (p = 0.028) and motility (p = 0.015) rates. These diminutive differences translate to less than 1 min of additional awake and motility time for a 5 dBA increase over a 450 min sleep period time. Overall results showed that wind turbine SPL below 45 dBA was not associated with any consequential changes in actigraphy-measured sleep. Observations based on ∆SPL provided some indication that a more sensitive assessment of sleep may be one that considers variations in wind turbine SPL throughout the sleep period time.

It has been reported that adult ostriches displayed the longest episodes of rapid eye movement (REM) sleep (up to 5 min) and more REM sleep (24% of the nighttime) than any other bird species. If the mammalian ontogenetic trend exists in the ostrich, then the amounts of REM and the duration of sleep episodes in young ostriches may be greater than those reported in adults. We investigated sleep in 1.5–3.5 month old ostrich chicks. Recordings were conducted during nighttime (20:00–08:00), the main sleep period in ostriches, which are diurnal. The polygrams were scored in 4-s epochs for waking, non-rapid eye movement (NREM) sleep and REM sleep, as in other bird studies. REM sleep in ostrich chicks occurred during both cortical EEG activation and during slow waves, as was described in adult ostriches. The chicks spent 69.3% ± 1.5% of the night in NREM sleep. REM sleep occupied 14.1% ± 1.8% of the night or 16.8% ± 2.0% of nighttime sleep. Episodes of REM sleep lasted on average 10 ± 1 s and ranged between 4 and 40 s. Therefore, the total amount and duration of REM sleep episodes in ostrich chicks were substantially smaller than reported in adult ostriches while the amounts of NREM sleep did not greatly differ. The developmental profile of REM sleep ontogenesis in the ostrich may be remarkably different from what has been reported in all studied mammals and birds.

International audience; The objective of the present study was to confirm the link between spontaneous smiling and active sleep in newborns, and to identify the role of the cortex in the generation of spontaneous smiles. A total of 12 healthy newborns born at term and three infants with major congenital abnormalities (two with hydranencephaly and one with a left hemispherectomy) were evaluated by video and polysomnography during a 3-hr sleep period. Smiles were graded and their association with isolated rapid eye movements and grouped rapid eye movements was analysed. In all, 383 smiles were recorded of which 377 occurred during active sleep. Smiles were shown to be significantly associated with active sleep (p

International audience; Memory formation is a dynamic process and sleep is part of it. Consolidation of memories relies on finely orchestrated brain activities occurring during the post-learning sleep period. In this issue of Neuron, Kumar and colleagues provide evidence that the activity of adult-born hippocampal neurons, during REM sleep, is critical for the consolidation of episodic memory.

Chronic short sleep or extended wake periods are commonly observed in most industrialized countries. Previously neurobehavioral impairment following sleep loss was considered to be a readily reversible occurrence, normalized upon recovery sleep. Recent clinical studies suggest that chronic short sleep and sleep disruption may be risk factors for neurodegeneration. Animal models have been instrumental in determining whether disturbed sleep can injure the brain. We now understand that repeated periods of extended wakefulness across the typical sleep period and/or sleep fragmentation can have lasting effects on neurogenesis and select populations of neurons and glia. Here we provide a comprehensive overview of the advancements made using animal models of sleep loss to understand the extent and mechanisms of chronic short sleep induced neural injury.

Sleep-disordered breathing (SDB) is a well-known risk factor for cardiovascular outcomes. Studies of patients with SDB have identified frequent night-time urination as a manifestation related to SDB. We aimed to clarify whether night-time frequency of urination is independently associated with SDB in a general population. We also investigated whether night-time frequency of urination can help presumptive diagnose SDB.Study participants consisted of 7151 community residents. Oxygen saturation during sleep was measured for four nights using a pulse oximeter. SDB was defined as ≥15 events per hour in which oxygen desaturation exceeded or equal to 3% during an actigraphy-determined sleep period. Night-time frequency of urination was recorded for one week using a sleep diary.Significant positive correlations were evident between night-time frequency of urination and SDB (none, 5.8%; once/night, 14.1%; twice/night, 20.1%; thrice/night, 28.7%;thrice/night, 44.1%, P 0.001). This association was independent of possible covariates, including sleep duration (adjusted odds ratio: once/night = 1.50, twice/night = 2.15, thrice/night = 3.07,thrice/night = 3.73, P 0.001). Other factors significantly associated with SDB were age, sex, obesity, observation of sleep apnea, and short sleep duration. The area under the curve of the risk score for SDB consisting of these conventional six items (0.834) significantly improved (0.842, P = 0.001) when night-time frequency of urination was considered as a risk score item.Night-time frequency of urination was associated with SDB. Our findings suggest that the urination frequency should be considered a manifestation of SDB even in a general population.

Anecdotal reports recount of individuals obtaining insights during sleep. For instance, various acclaimed scientists have attributed some of their greatest insights to sleep-related mentation. To date, this phenomenon has not been systematically investigated. The current study explored the occurrence and characteristics of Sleep-Related Insights (SRIs) in a large population sample, using a questionnaire approach. We found that a large majority of participants (~80%) experienced SRIs at some point in their lives and about 40% obtained SRIs regularly. Most of these subjects could link SRIs to remembered sleep mentation. SRIs were reported to occur in both sleep and half-sleep states, and at any point of the sleep period. Furthermore, SRIs regarded emotional preoccupations about twice as often as theoretical problems. Finally, SRIs were not robustly related to subjective sleep-quality, but small positive correlations with insomnia and narcolepsy-like symptoms were observed. In conclusion, SRIs are much more common than might have been expected, manifest in several forms and appear to be part of normal, healthy sleep. Importantly, the strong link of SRIs with sleep mentation suggests they result from some form of higher-order information processing during sleep, rather than being (fully) secondary to general restorative effects of sleep. Finally, our findings show that a large portion of the sampled population is aware of sleep's benefits for real life problem solving and experiences such benefits on a regular basis.

The purpose of this study was to test whether estimates of bedtime, wake time, and sleep period time (SPT) were comparable between an automated algorithm (ALG) applied to waist-worn accelerometry data and a sleep log (LOG) in an adult sample. A total of 104 participants were asked to log evening bedtime and morning wake time and wear an ActiGraph wGT3X-BT accelerometer at their waist for 24 h/day for 7 consecutive days. Mean difference and mean absolute difference (MAD) were computed. Pearson correlations and dependent-sample t tests were used to compare LOG-based and ALG-based sleep variables. Effect sizes were calculated for variables with significant mean differences. A total of 84 participants provided 2+ days of valid accelerometer and LOG data for a total of 368 days. There was no mean difference (p = 0.47) between LOG 472 ± 59 min and ALG SPT 475 ± 66 min (MAD = 31 ± 23 min, r = 0.81). There was no significant mean difference between bedtime (2348 h and 2353 h for LOG and ALG, respectively; p = 0.14, MAD = 25 ± 21 min, r = 0.92). However, there was a significant mean difference between LOG (0741 h) and ALG (0749 h) wake times (p = 0.01, d = 0.11, MAD = 24 ± 21 min, r = 0.92). The LOG and ALG data were highly correlated and relatively small differences were present. The significant mean difference in wake time might not be practically meaningful (Cohen’s d = 0.11), making the ALG useful for sample estimates. MAD, which gives a better estimate of the expected differences at the individual level, also demonstrated good evidence supporting ALG individual estimates.

Wrist worn raw-data accelerometers are used increasingly in large-scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window) was compared against sleep diary in 3752 participants (range = 60–82 years) and polysomnography in sleep clinic patients (N = 28) and in healthy good sleepers (N = 22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.

Brooke, SM, An, H-S, Kang, S-K, Noble, JM, Berg, KE, and Lee, J-M. Concurrent validity of wearable activity trackers under free-living conditions. J Strength Cond Res 31(4): 1097-1106, 2017-The purpose of this study is to evaluate the concurrent validity of wearable activity trackers in energy expenditure (EE) and sleep period time (SPT) under free-living conditions. Ninety-five (28.5 ± 9.8 years) healthy men (n = 34) and women (n = 61) participated in this study. The total EE and SPT were measured using 8 monitors: Nike+ FuelBand SE (NFB), Garmin VivoFit (VF), Misfit Shine (MF), Fitbit Flex (FF), Jawbone UP (JU), Polar Loop (PL), Fitbit Charge HR (FC), and SenseWear Armband Mini (SWA) (criterion measures: SWA for EE and a sleep log for SPT). The mean absolute percent error (MAPE) for EE was 13.0, 15.2, 15.5, 16.1, 16.2, 22.8, and 24.5% for PL, MF, FF, NFB, FC, JU, and VF, respectively. Mean absolute percent errors were calculated for SPT to be 4.0, 8.8, 10.2, 11.5, 12.9, 13.6, 17.5, and 21.61% for VF, FF, JU, FC, MF, SWA laying down, PL, and SWA, respectively. Concurrent validity was examined using equivalence testing on EE (equivalence zone: 2,889.7-3,531.9 kcal); 2 trackers fell short of falling in the zone: PL (2,714.4-3,164.8 kcal) and FC (2,473.8-3,066.5 kcal). For SPT (equivalence zone: 420.6-514.0 minutes), several monitors fell in the zone: PL (448.3-485.6 minutes), MS (442.8-492.2 minutes), and FF (427.7-486.7 minutes). This study suggests that the PL and FC provide a reasonable estimate of EE under free-living conditions. The PL, FC, and MF were the most valid monitors used for measuring SPT.

To assess the association between sleep period time and dietary patterns (DPs) in Brazilian schoolchildren aged 7-13 years.Sleep data of 1019 children were obtained from a questionnaire completed by parents/guardians. Food consumption, physical activity, and screen-based activity were assessed through the validated Web-CAAFE questionnaire. Latent profile analysis was used to identify dietary patterns. Associations between sleep period time and dietary patterns were analyzed by multinomial logistic regression, and the average marginal effect of sleep period time on the probability of adherence to dietary patterns was determined.Overall, 11.4% of children had inadequate sleep period time (9 h per day). Three mutually exclusive dietary patterns were identified: "Monotonous" characterized by high consumption of pasta, instant pasta, sweets, and hamburgers/hot dog/pizza/salty snacks; "Traditional" characterized by high consumption of rice, vegetables, green leaves, beans, manioc flour, maize/potatoes, and meats; and "Dairy, bread, green leaves, maize/potatoes and sausage". The likelihood of adherence to the "Dairy, bread, green leaves, maize/potatoes and sausages" DP decreased by 0.026 as sleep period time increased by 1 h per day. For a sleep period time of more than 10 h per day, the average marginal effect of sleep period time on the likelihood of adherence to the this dietary pattern was significant and negative.Sleep period time was inversely associated with adherence to the "Dairy, bread, green leaves, maize/potatoes and sausages" DP; children who slept more than 10 h per day were less likely to present this pattern.

Study Objectives To compare rail workers’ actual sleep–wake behaviors in normal operations to those predicted by a biomathematical model of fatigue (BMMF). To determine whether there are group-level residual sources of error in sleep predictions that could be modeled to improve group-level sleep predictions. Methods The sleep–wake behaviors of 354 rail workers were examined during 1,722 breaks that were 8–24 h in duration. Sleep–wake patterns were continuously monitored using wrist-actigraphy and predicted from the work–rest schedule using a BMMF. Rail workers’ actual and predicted sleep–wake behaviors were defined as split-sleep (i.e. ≥2 sleep periods in a break) and consolidated-sleep (i.e. one sleep period in a break) behaviors. Sleepiness was predicted from the actual and predicted sleep–wake data. Results Consolidated-sleep behaviors were observed during 1,441 breaks and correctly predicted during 1,359 breaks. Split-sleep behaviors were observed during 280 breaks and correctly predicted during 182 breaks. Predicting the wrong type of sleep–wake behavior resulted in a misestimation of hours of sleep during a break. Relative to sleepiness predictions derived from actual sleep–wake data, predicting the wrong type of sleep–wake behavior resulted in a misestimation of sleepiness predictions during the subsequent shift. Conclusions All workers with the same work–rest schedule have the same predicted sleep–wake behaviors; however, these workers do not all exhibit the same sleep–wake behaviors in real-world operations. Future models could account for this group-level residual variance with a new approach to modeling sleep, whereby sub-group(s) may be predicted to exhibit one of a number of sleep–wake behaviors.

Simple Summary Humans commonly share their beds with companion animals, yet little is known regarding how pets impact sleep. In survey-based studies, pet owners report that their dogs favorably affect sleep quality, but prior actigraphy-based studies of human-dog co-sleeping have concluded the practice can lead to sleep arousals and disturbances and, thus, reduce sleep efficiency (i.e., the ratio of time spent asleep in a night as compared to the time spent in bed). We examined actigraphy data from women and dogs and sleep diary data to investigate the apparent disconnect between objective and subjective reports regarding dogs’ effects on sleep. We also analyzed data minute-by-minute to assess whether dog movement impacted the likelihood the human would transition from an inactive to active state. We found associations between human and dog movement over sleep periods and that dogs influenced human movement more than humans influenced dog movement. Humans were largely unaware of their dog’s nighttime movements, and they rarely reported that their dog awakened them during the night. Additional research on more diverse samples and studies that use polysomnography and behavioral observations are necessary for developing a better understanding of how pets affect the quality of human sleep. Abstract Humans regularly enter into co-sleeping arrangements with human and non-human partners. Studies of adults who co-sleep report that co-sleeping can impact sleep quality, particularly for women. Although dog owners often choose to bedshare with their dogs, we know relatively little about the nature of these relationships, nor the extent to which co-sleeping might interfere with sleep quality or quantity. In an effort to rectify this, we selected a sample of 12 adult female human (M = 50.8 years) and dog dyads, and monitored their activity using actigraphy. We collected movement data in one-minute epochs for each sleep period for an average of 10 nights per participant. This resulted in 124 nights of data, covering 54,533 observations (M = 7.3 hours per night). In addition, we collected subjective sleep diary data from human participants. We found a significant positive relationship between human and dog movement over sleep periods, with dogs influencing human movement more than humans influenced dog movement. Dog movement accompanied approximately 50% of human movement observations, and dog movement tripled the likelihood of the human transitioning from a non-moving state to a moving state. Nevertheless, humans rarely reported that their dog disrupted their sleep. We encourage the continued exploration of human-animal co-sleeping in all its facets and provide recommendations for future research in this area.

Objective Recent findings suggested that subclinical epileptiform activity is prevalent during sleep in a significant proportion of Alzheimer’s Disease (AD) patients. The aims of our study were: (A) comparing the frequency of subclinical epileptiform activity during the sleep in a sample diagnosed with ‘probable’ AD and Mild Cognitive Impairment (MCI) due to AD, and in healthy subjects; (B) evaluating epileptiform EEG activity as a function of different sleep stages within a well-controlled polysomnographic setting. Methods We prospectively enrolled 50 ‘probable’ AD patients (73 ± 7.0 years) and 50 subjects with MCI due to AD (72 ± 6.7 years) without history of seizures, comparing them with 50 controls (69 ± 6.7 years). Patients underwent to a full-night video-PSG. Results Subclinical epileptiform activity was detected in 6.38% of ‘probable’ AD patients, 11.63% of MCI due to AD subjects and 4.54% of controls (p = 0.43). The comparisons between the three groups for the frequency of epileptiform activity did not reach statistically significant differences neither for total sleep nor for any sleep period considered. Conclusions Our study shows that, when controlling for sleep stages and the influence of psychoactive drugs, AD patients and MCI due to AD subjects do not exhibit a higher frequency of epileptiform discharges during sleep compared to healthy subjects. Significance Subclinical epileptiform activity during sleep does not discriminate ‘probable’ AD from MCI due to AD and healthy controls.

Background Results from human experimental studies investigating possible effects of radiofrequency electromagnetic fields (RF-EMF) on sleep are heterogeneous. So far, there is no study on possible sex-differences in RF-EMF effects. Objectives The present study aimed at analyzing differences in RF-EMF effects on the macrostructure of sleep between healthy elderly males and females. Methods With a double-blind, randomized, sham-controlled cross-over design effects of two RF-EMF exposures (GSM900 and TETRA) on sleep were investigated in samples of 30 elderly healthy male and 30 healthy elderly female volunteers. Participants underwent each of the three exposure conditions on three occassions following an individually randomized order resulting in a total of nine study nights per participant. Exposure was delivered for 30 min prior to sleep and for the whole night (7.5 h) by a head worn antenna specifically designed for the projects. The peak spatial absorption rate averaged over time in head tissues (psSAR10g) was 6 W/kg for TETRA and 2 W/kg for GSM900. Thirty variables characterising the macrostructure of sleep and arousals as well as four subjective sleep variables were considered for statistical analyses. Results Multivariate analyses revealed that exposure to GSM900 and/or TETRA resulted in a significant reduction in arousals, a shorter latency to sleep stage N3, and a shorter self-reported time awake after sleep in both males and females. Exposure effects depending on sex (significant interactions) were observed. Latency to sleep stage R was shorter in females and tended to be longer in males under both exposures. Latency to stage N3 was shorter in females under TETRA exposure and almost not affected in males. The time awake within the sleep period under TETRA exposure was shorter in females and only slightly longer in males. Under GSM exposure, the self-rated total sleep time tended to be longer in females and to be shorter in males. Finally, the number of awakenings was lower only in females and tended to be higher in males under GSM exposure. Discussion With regard to RF-EMF effects on human sleep it seems that gender matters since GSM900 and TETRA led to significantly more exposure effects in females. Regardless of gender, none of the observed changes is indicative of a sleep disturbing effect of RF-EMF exposure. Observed effects might be mediated by skin related thermoregulatory mechanisms.

We proposed and tested a method to estimate sleep period time (SPT) using electrodermal activity (EDA) signals. Eight healthy subjects and six obstructive sleep apnea patients participated in the experiments. Each subject's EDA signals were measured at the middle and ring fingers of the dominant hand during polysomnography (PSG). For nine of the 17 participants, wrist actigraphy was also measured for a quantitative comparison of EDA- and actigraphy-based methods. Based on the training data, we observed that sleep onset was accompanied by a gradual reduction of amplitude of the EDA signals, whereas sleep offset was accompanied by a rapid increase in amplitude of EDA signals. We developed a method based on these EDA fluctuations during sleep-wake transitions, and applied it to a test dataset. The performance of the method was assessed by comparing its results with those from a physician's sleep stage scores. The mean absolute errors in the obtained values for sleep onset, offset, and period time between the proposed method, and the results of the PSG were 4.1, 3.0, and 6.1 min, respectively. Furthermore, there were no significant differences in the corresponding values between the methods. We compared these results with those obtained by applying actigraphic methods, and found that our algorithm outperformed these in terms of each estimated parameter of interest in SPT estimation. Long awakening periods were also detected based on sympathetic responses reflected in the EDA signals. The proposed method can be applied to a daily sleep monitoring system.

Objective/Background Recent technological advances and emerging commercially-available consumer-friendly sleep assessment products affords researchers with a host of tools to consider for capturing free-living sleep in children. The purpose of this study was to compare free-living sleep characteristics (duration and bed/wake times) across different measures in children. Methods Elementary school-aged children (N = 30, mean age 7.2 years, 63% boys, 87% non-Hispanic white) wore an ActiGraph GT9X Link© and Fitbit Charge HR© on the non-dominant wrist, with a Beddit 3 Sleep Monitor© affixed to their mattress for two consecutive weekend nights of free-living sleep. Parents completed a sleep log of bed and wake times. Absolute differences in bed and wake times were examined and Bland Altman plots assessed the level of agreement across sleep measures. Results Across the four sleep measures, total sleep time (TST) ranged from 458 min/night (ActiGraph GT9X Link©) to 613 min/night (Parent report). Mean bed and wake times ranged from 8:46PM to 9:03PM, and 6:52AM to 7:16AM, respectively. Pearson correlation coefficients were moderate between all four sleep measures (range r = 0.30–0.71). Bland–Altman plots indicated the highest level of agreement for TST was between Beddit 3 Sleep Monitor© and Fitbit Charge HR© (mean difference −11.7, limits of agreement: 119.0, −142.4 min). Conclusions The findings from this study show a high level of agreement of when a child goes to sleep and wakes up across a variety of sleep measures; however, more work is needed to classify TST once the sleep period has commenced.

Objectives Many studies of infant sleep rely solely on parentally-reported data, assuming that parents accurately report their infant's sleep parameters. The objective of this paper is to examine whether night-time sleep parameters of exclusively breastfed or exclusively formula-fed infants differ, and whether correspondence between parental reports and objective measures varies by feeding type. Methods Mother-infant dyads intending to breastfeed or formula-feed exclusively for 18 weeks were recruited. Mothers were multiparas and primiparas, aged between 18 and 45 years. Infants were full-term, normal birthweight singletons. Maternal report and actigraphic data on infant sleep were collected fortnightly, from four to 18 weeks postpartum. Data were analysed cross-sectionally using t-tests and GLM analysis to control for interaction between feed-type and sleep location. Results Actigraphy-assessed infant sleep parameters did not vary by feed-type but parentally reported sleep parameters did. Maternal report and actigraphy data diverged at 10 weeks postpartum and discrepancies were associated with infant feeding type. Compared to actigraphy, maternal reports by formula-feeding mothers (controlling for infant sleep location) over-estimated infant's Total Sleep Time (TST) at 10 weeks and Longest Sleep Period (LSP) at 10, 12 and 18 weeks. Conclusions These results raise questions about the outcomes of previous infant sleep studies where accuracy of parentally-reported infant sleep data is assumed. That parental reports of infant sleep vary by feeding type is particularly important for reconsidering previous studies of infant sleep development and intervention studies designed to influence sleep outcomes, especially where feed-type was heterogeneous, but was not considered as an independent variable.

Objectives We investigated physical activity as a moderator of relations between sleep duration and quality and adolescents' internalizing and externalizing problems. Design The study used a cross-sectional design. Setting Participants were recruited from small towns and semi-urban communities in Alabama. Participants The sample was comprised of 235 adolescents (Mage = 15.78 years, SD = 9.60 months) who were diverse in sex (53% female), race/ethnicity (34% Black/African American, 66% White), and socioeconomic status. Measurements Sleep duration (actual sleep minutes), efficiency (minutes/total sleep period), and latency (minutes from sleep attempt to onset) were examined with actigraphs for 1 week. Youth reported on their physical activity levels and internalizing and externalizing problems. Results Interactions between sleep and physical activity emerged in the prediction of adolescents' internalizing and externalizing problems. Supportive of moderation effects, adolescents with shorter or poorer-quality sleep in conjunction with less physical activity showed the highest levels of internalizing and externalizing problems. Demonstrative of protective effects, adolescents with more physical activity had lower levels of internalizing and externalizing problems regardless of their sleep duration or quality. Conclusions Findings illustrate that not all youth are at equal risk for adjustment problems when they experience short or poor-quality sleep, suggesting the importance of examining both bioregulatory and environmental factors in understanding adolescent adjustment.

OBJECTIVES The aims of the present study were (i) to develop automated algorithms to identify the sleep period time in 24 h data from the Intelligent Device for Energy Expenditure and Activity (IDEEA) in older adults, and (ii) to analyze the agreement between these algorithms to identify the sleep period time as compared to self-reported data and expert visual analysis of accelerometer raw data. APPROACH This study comprised 50 participants, aged 65-85 years. Fourteen automated algorithms were developed. Participants reported their bedtime and waking time on the days on which they wore the device. A well-trained expert reviewed each IDEEA file in order to visually identify bedtime and waking time on each day. To explore the agreement between methods, Pearson correlations, mean differences, mean percentage errors, accuracy, sensitivity and specificity, and the Bland-Altman method were calculated. MAIN RESULTS With 87 d of valid data, algorithms 6, 7, 11 and 12 achieved higher levels of agreement in determining sleep period time when compared to self-reported data (mean difference = -0.34 to 0.01 h d-1; mean absolute error = 10.66%-11.44%; r = 0.515-0.686; accuracy = 95.0%-95.6%; sensitivity = 93.0%-95.8%; specificity = 95.7%-96.4%) and expert visual analysis (mean difference = -0.04 to 0.31 h d-1; mean absolute error = 5.0%-6.97%; r = 0.620-0.766; accuracy = 97.2%-98.0%; sensitivity = 94.5%-97.6%; specificity = 98.4%-98.8%). Bland-Altman plots showed no systematic biases in these comparisons (all p > 0.05). Differences between methods did not vary significantly by gender, age, obesity, self-rated health, or the presence of chronic conditions. SIGNIFICANCE These four algorithms can be used to identify easily and with adequate accuracy the sleep period time using the IDEEA activity monitor from 24 h free-living data in older adults.

International audience; OBJECTIVES: The goal of this project was to provisionally identify the basic elements of sleep satisfaction within the general population. METHODS: The National Sleep Foundation conducted a systematic literature review and identified 495 published articles evaluating potential indicators of sleep satisfaction. The National Sleep Foundation then convened an expert panel ("Panel"), provided full-text articles and summaries, and used a modified RAND appropriateness method with three total rounds of voting to determine the appropriateness of indicators for sleep satisfaction. RESULTS: The literature review revealed no tools or measures of sleep satisfaction (not dissatisfaction) applied to the general population and directly associated with good health. Nonetheless, a variety of sleep factors were extracted from the extant sleep research literature. Panel members voted on these indicators: sleep environmental factors; and sleep initiation and maintenance parameters. Using these indicators, the Panel constructed provisional questions for measuring sleep satisfaction. CONCLUSIONS: The Panel determined that appropriate sleep satisfaction elements include how an individual feels (a) about their sleep, (b) immediately after their sleep, and (c) during the subsequent day. Additionally, appropriate environmental elements include (a) bedding comfort, (b) bedroom temperature, and (c) noise and light in the bedroom. How one feels with (a) the time it takes to fall asleep, (b) the ease with which one falls back to sleep after awakening during a sleep period, (c) the amount of sleep on weekdays and weekends, as well as how undisturbed one's sleep is also were determined to be appropriate contributors to sleep satisfaction. Finally, the Panel agreed that whether an individual desired to change anything about their sleep, is a relevant question.

This study assessed infant sleep-wake behavior at two weeks, three and six months as function of feeding method at three months (exclusively breastfed, partially breastfed, and exclusively formula fed infants). Mothers of 163 first-born, full-term, normal birth weight, healthy infants completed socio-demographic, depression, anxiety, and infant sleep-wake behavior measures. No effects were found for sleep arrangements, depression or anxiety, on feeding methods and sleep-wake behavior at three months. At two weeks exclusively breastfed infants at three months spent more hours sleeping and less hours awake during the 24-h period than partially breastfed infants. At three months, exclusively breastfed infants had a shorter of the longest sleep period at night than exclusively formula fed infants. At six months, exclusively breastfed infants at three months spent more hours awake at night than partially breastfed infants, awake more at night than exclusively formula fed infants, and had a shorter sleep period at night than partially breastfed and exclusively formula fed infants. This study showed differences in sleep-wake behaviors at two weeks, three and six months, when exclusively breastfed infants are compared with partially breastfed and exclusively formula fed infants at three months, while no effects were found for sleep arrangements, depression or anxiety., PTDC/SAU/SAP/116738/2010; SFRH/BSAB/14445/2014; POCI-01-0145-FEDER-007653, info:eu-repo/semantics/publishedVersion

Technology-supported methods for sleep recording are becoming increasingly affordable. Sleep history feedback may help with fatigue-related decision making - Should I drive? Am I fit for work? This study examines a "sleep tank" model (SleepTank ™ ), which is analogous to the fuel tank in a car, refilled by sleep, and depleted during wake. Required inputs are sleep period time and sleep efficiency (provided by many consumer-grade actigraphs). Outputs include suggested hours remaining to "get sleep" and percentage remaining in tank (Tank%). Initial proof of co ncept analyses were conducted using data from a laboratory-based simulated nightshift study. Ten, healthy males (18-35y) undertook an 8h baseline sleep opportunity and daytime performance testing (BL), followed by four simulated nightshifts (2000 h-0600 h), with daytime sleep opportunities (1000 h-1600 h), then an 8 h night-time sleep opportunity to return to daytime schedule (RTDS), followed by daytime performance testing. Psychomotor Vigilance Task (PVT) and Karolinska Sleepiness Scale were performed at 1200 h on BL and RTDS, and at 1830 h, 2130 h 0000 h and 0400 h each nightshift. A 40-minute York Driving Simulation was performed at 1730 h, 2030 h and 0300 h on each nightshift. Model outputs were calculated using sleep period timing and sleep efficiency (from polysomnography) for each participant. Tank% was a significant predictor of PVT lapses (p < 0.001), and KSS (p < 0.001), such that every 5% reduction resulted in an increase of two lapses, or one point on the KSS. Tank% was also a significant predictor of %time in the Safe Zone from the driving simulator (p = 0.001), such that every 1% increase in the tank resulted in a 0.75% increase in time spent in the Safe Zone. Initial examination of the correspondence between model predictions and performance and sleepiness measures indicated relatively good predictive value. Results provide tentative evidence that this "sleep tank" model may be an informative tool to aid in individual decision-making based on sleep history. Refereed/Peer-reviewed

Monthly rhythms in the body core temperature of women during sleep can provide significant information concerning hormonal fluctuations. The purpose of the present study was to examine and evaluate auditory canal temperature (Tauditory), measured with a newly-developed wearable and wireless device, as a practical index to estimate body core temperature variations during a 7-h sleep period. Comparisons with rectal temperature (Tre) at different depths were conducted. Nine young females slept in a climate chamber at an air temperature of 27 °C with 50% relative humidity. Rectal temperatures at 6, 10 and 14 cm depths, as well as partially insulated Tauditory were simultaneously measured every 5 s during sleep. The results showed that Tauditory was, on average, 0.32 °C lower than Tre at 14 cm depth (P = 0.010), while significant relationships between Tauditory and Tre at 10 cm (r2 = 0.634, P = 0.010), and at 14 cm depths were also found (r2 = 0.826, P = 0.001). Rectal temperatures at 6 cm and 10 cm depths fell between those of Tauditory and Tre at 14 cm. We concluded that Tauditory, as measured using the newly-developed wearable device, can be a reliable, practical and continuous estimate of body core temperature during sleep.

Although most research on sleep and adolescent health has focused on how long each youth sleeps on average, variability in sleep duration may be just as problematic. Existing findings have been inconsistent and unable to address cause-effect relationships. This study piloted an experimental protocol to induce sleep variability and explore its impact on daytime sleepiness in adolescents. Healthy adolescents aged 14–17 participated in a 3-week, at-home protocol. Sleep was monitored by sleep diaries and actigraphy. Following a run-in period to stabilize wake times (set at 6:30am throughout the protocol), participants were randomly counterbalanced across two 5-night experimental conditions. Bedtimes were consistent at 11:00pm during the stable sleep condition (7.5-hour sleep period each night) but changed on alternating nights during the variable sleep condition (ranging from 9:30pm to 12:30am) so that sleep duration averaged 7.5 hours across the condition with a standard deviation of 1.37 hours. Difficulty waking was assessed each morning and daytime sleepiness was assessed by end-of-condition parent- and adolescent-reports. Of the 20 participants who completed the study, 16 met the predetermined adherence definition. For those who were adherent, there were no differences in overall sleep duration between the stable and variable sleep conditions (p>.05) but adolescents had 58.6 minutes greater night-to-night variation in sleep duration in the variable condition (p < .001). Across all nights, youth reported greater difficulty waking following nights of shorter assigned sleep (p = .004) and greater overall sleepiness during the variable condition (p = .03). It is feasible to experimentally vary how long adolescents sleep on a nightly basis while holding average sleep duration constant. Such a protocol will promote tests of the acute effects of day-to-day changes in sleep duration on health.

Analysis of 24-h waist-worn accelerometer data for physical activity and sedentary behavior requires that sleep-period time (from sleep onset to the end of sleep, including all sleep epochs and wakefulness after onset) is first identified. To identify sleep-period time in children in this study, we evaluated the validity of a published automated algorithm that requires nonaccelerometer bed- and wake-time inputs, relative to a criterion expert visual analysis of minute-by-minute waist-worn accelerometer data, and validated a refined fully automated algorithm. Thirty grade 4 schoolchildren (50% girls) provided 24-h waist-worn accelerometry data. Expert visual inspection (criterion), a published algorithm (Algorithm 1), and 2 additional automated refinements (Algorithm 2, which draws on the instrument's inclinometer function, and Algorithm 3, which focuses on bedtime and wake time points) were applied to a standardized 24-h time block. Paired t tests were used to evaluate differences in mean sleep time (expert criterion minus algorithm estimate). Compared with the criterion, Algorithm 1 and Algorithm 2 significantly overestimated sleep time by 43 min and 90 min, respectively. Algorithm 3 produced the smallest mean difference (2 min), and was not significantly different from the criterion. Relative to expert visual inspection, our automated Algorithm 3 produced an estimate that was precise and within expected values for similarly aged children. This fully automated algorithm for 24-h waist-worn accelerometer data will facilitate the separation of sleep time from sedentary behavior and physical activity of all intensities during the remainder of the day.

Summary Background Gastro-oesophageal reflux disease (GERD) adversely impacts on sleep, but the mechanism remains unclear. Aim To review the literature concerning gastro-oesophageal reflux during the sleep period, with particular reference to the sleep/awake state at reflux onset. Methods Studies identified by systematic literature searches were assessed. Results Overall patterns of reflux during the sleep period show consistently that oesophageal acid clearance is slower, and reflux frequency and oesophageal acid exposure are higher in patients with GERD than in healthy individuals. Of the 17 mechanistic studies identified by the searches, 15 reported that a minority of reflux episodes occurred during stable sleep, but the prevailing sleep state at the onset of reflux in these studies remains unclear owing to insufficient temporal resolution of recording or analysis methods. Two studies, in healthy individuals and patients with GERD, analysed sleep and pH with adequate resolution for temporal alignment of sleep state and the onset of reflux: all 232 sleep period reflux episodes evaluated occurred during arousals from sleep lasting less than 15 s or during longer duration awakenings. Six mechanistic studies found that transient lower oesophageal sphincter relaxations were the most common mechanism of sleep period reflux. Conclusions Contrary to the prevailing view, subjective impairment of sleep in GERD is unlikely to be due to the occurrence of reflux during stable sleep, but could result from slow clearance of acid reflux that occurs during arousals or awakenings from sleep. Definitive studies are needed on the sleep/awake state at reflux onset across the full GERD spectrum.

Study Objectives: Sleep supports the consolidation of new memories. However, this effect has mainly been shown for memories of past events. Here we investigated the role of sleep for the implementation of intentions for the future. Design: Subjects were instructed on a plan that had to be executed after a delay of 2 days. After plan instruction, subjects were either allowed to sleep or stayed awake for one night (Exp. 1) or had a 3-h sleep period either during the early night (SWS-rich sleep) or late night (REM-rich sleep; Exp. 2). In both experiments, retesting took place 2 days later after one recovery night. Setting: Sleep laboratory. Patients or Participants: A total of 56 healthy young adults participated in the study. Interventions: N/A. Measurements and Results: All of the subjects who were allowed to sleep after plan instruction executed the intention 2 days later, whereas only 61% of wake subjects did so (P = 0.004; Exp. 1). Also after early SWS-rich sleep all of the subjects remembered to execute the intention, but only 55% did so after late REM-rich sleep (P = 0.015; Exp. 2). Conclusions: Sleep, especially SWS, plays an important role for the successful implementation of delayed intentions.

Acoustic stimulation methods applied during sleep in young adults can increase slow wave activity (SWA) and improve sleep-dependent memory retention. It is unknown whether this approach enhances SWA and memory in older adults, who generally have reduced SWA compared to younger adults. Additionally, older adults are at risk for age-related cognitive impairment and therefore may benefit from non-invasive interventions. The aim of this study was to determine if acoustic stimulation can increase SWA and improve declarative memory in healthy older adults. Thirteen participants 60–84 years old completed one night of acoustic stimulation and one night of sham stimulation in random order. During sleep, a real-time algorithm using an adaptive phase-locked loop modeled the phase of endogenous slow waves in midline frontopolar electroencephalographic recordings. Pulses of pink noise were delivered when the upstate of the slow wave was predicted. Each interval of five pulses (“ON interval”) was followed by a pause of approximately equal length (“OFF interval”). SWA during the entire sleep period was similar between stimulation and sham conditions, whereas SWA and spindle activity were increased during ON intervals compared to matched periods during the sham night. The increases in SWA and spindle activity were sustained across almost the entire five-pulse ON interval compared to matched sham periods. Verbal paired-associate memory was tested before and after sleep. Overnight improvement in word recall was significantly greater with acoustic stimulation compared to sham and was correlated with changes in SWA between ON and OFF intervals. Using the phase-locked-loop method to precisely target acoustic stimulation to the upstate of sleep slow oscillations, we were able to enhance SWA and improve sleep-dependent memory storage in older adults, which strengthens the theoretical link between sleep and age-related memory integrity.

We examined the pattern of cytokine secretion across the 24-hr day for women with widespread pain and tenderness having the diagnosis of fibromyalgia (FM) and matched healthy controls. Subjects were given time to habituate to being in a clinical research laboratory environment and then were sampled for cytokines without their being disturbed for a 24-hr period including an 8-hr sleep period. Cytokine levels were uniformly low but characterized by bursts of secretion. Bursting occurred either in singlets or in doublets with a range from 88 to 131 mins between doublet bursts. There was an element of synchronization of these bursts with most occurring at the beginning of sampling. FM patients showed a shift to increased IL-10 in the nighttime compared to controls. The relation between this anti-inflammatory cytokine to the pro-inflammatory cytokines studied also differed between groups: FM patients showed an increased ratio of IL-10 burst amplitude to that of pro-inflammatory cytokines IL-1β, IL-8, and TNF-α. We interpret this to indicate a skew away from the normal balance favoring pro-inflammatory cytokines in controls toward one favoring an anti-inflammatory response in FM. These changes toward anti-inflammatory predominance in FM may explain their common complaint of disturbed sleep because these cytokines are known to disrupt sleep.

Background It has been suggested that impaired dissipation of slow-wave activity (SWA) in children with sleep-disordered breathing (SDB) may be a potential mechanism for daytime dysfunction. We aimed to examine whether resolution of SDB resulted in normalisation of SWA dissipation and whether this was associated with improved cognition and behaviour. Methods Children (aged 3–6 y) diagnosed with SDB and age-matched non-snoring control children were followed up for 3 y after a baseline study. At the follow-up, children were categorised into control (N = 13), resolved SDB (N = 15) and unresolved SDB (N = 14). Delta activity on the electroencephalogram over the sleep period was used to calculate SWA and a battery of cognitive assessments and behaviour questionnaires were conducted at both time points. Results There was no change in the average SWA between the baseline and follow-up and no differences between the groups. Cognitive and behavioural performance in the resolved group did not improve to control levels. However, decreased SWA at the beginning of the sleep period (β = −0.04, p = 0.002) and a decrease in obstructive apnoea–hypopnoea index (β = −2.2, p = 0.022) between the baseline and follow-up predicted improvements in measures of sustained attention. Increased SWA at the beginning of the sleep period between the baseline and follow-up predicted worsening of externalising behaviour (β = 0.02, p = 0.039). Conclusions This study suggests that resolution of SDB is not associated with changes in the dissipation of SWA. However, the association between decreases in SWA and improvements in cognitive and behavioural outcomes suggest that irrespective of disease, children whose quantitative sleepiness improves have improved attention and reduced externalising behaviours.

Sleep may play a role in consolidating emotional memories. However, studies on the effects of REM sleep on negative vs. neutral memories have produced inconsistent evidence. Here, we assess the role of NREM and REM sleep before and after learning in promoting the consolidation of neutral and arousing pleasant and unpleasant memories. Forty-six (32 F) healthy university students were exposed to a set of pictures at 1:00PM (Session 1) and to an equivalent set at 4:45PM (Session 2). All the pictures in Session 1 and Session 2 were presented again, intermixed with new similar pictures at 5:15PM in a memory recognition task. Following Session 1, participants took a 90/120-min nap (NAP group), while 16 participants remained awake (WAKE group). Via polysomnographic recording, the NAP group was segregated into REM (N=14) and NoREM groups (N=16). Indices of memory consolidation for both stimuli presented before (discriminability of Session 1 pictures in Session 3) and after sleep (discriminability of Session 2 pictures in Session 3) were calculated. Memory consolidation for pictures presented both before and after the sleep period was higher in the NAP group as compared to the WAKE group, but no differential role of REM sleep emerged. A memory consolidation advantage was evident for neutral over pleasant (but not unpleasant) pictures. Taken together, these results indicate that a daytime nap (with or without REM sleep) facilitates consolidation of declarative memories presented before and after sleep irrespective of their valence.

Although infant sleep-wake behavior presents several developmental changes during the first six months, literature lacks on reference values and few studies have explored the role of individual change and stability on infant sleep-wake behavior during the first six months. This study aimed (1) to describe infant sleep-wake behaviors during the 24-h period, day and night, at two weeks, three, and six months, (2) and to explore developmental changes and the role of individual change and stability on infant sleep-wake behaviors from two weeks to six months. Ninety-four primiparous mothers completed measures on infant sleep-wake behaviors at two weeks, three and six months. Significant developmental changes were found on infant sleep-wake behaviors from two weeks to six months. Twoweek- old infants sleep 13.3 h, spend 8.7 h awake, awake 6.1 times, have 0.4 h of latency to sleep, and 3.2 h of longest sleep period. Three-month-old infants sleep 13.0 h, spend 9.2 h awake, awake 5.5 times, have 0.4 h of latency to sleep, and 5.2 h of longest sleep period. Sixmonth- old infants sleep 12.2 h, spend 10.0 h awake, awake 5.2 times, have 0.4 h of latency to sleep, and 5.6 h of longest sleep period. Significant individual change and stability were also found on infant sleep-wake behaviors from two weeks to six months. Despite significant developmental and individual changes, individual stability explains a significant amount of the variance on infant sleep-wake behaviors over the first six months of life., FEDER Funds through the Programa Operacional Factores de Competitividade − COMPETE and by National Funds through FCT − Fundação para a Ciência e a Tecnologia under the project: PTDC/SAU/SAP/116738/2010 and SFRH/BSAB/14445/2014 grant, Portuguese Foundation for Science and Technology and the Portuguese Ministry of Education and Science through national funds and co-financed by FEDER through COMPETE2020 under the PT2020 Partnership Agreement (POCI-01-0145- FEDER-007653), Psychology Research Centre (UID/PSI/01662/2013), University of Minho

The physiologic function of nasal nitric oxide (NO) release is unknown. In prior experiments, topical NG-nitro- l -arginine methyl ester ( l -NAME) on nasal mucosa reduced exhaled nasal NO output and caused daytime sleepiness. We hypothesized that nasal NO output is reduced at night during the sleep period. We measured exhaled nasal NO concentration and minute ventilation and calculated nasal NO output in humans over 24 h. Daytime awake NO output was greater than NO output at night during sleep or transient wakefulness. Exhaled NO concentration decreased during sleep along with minute ventilation. A daytime voluntary reduction in minute ventilation also decreased nasal NO output but exhaled NO concentration increased. Nasal NO output was not changed by body position. We conclude that exhaled nasal NO output is decreased at night due to decreased mass flow of NO into nasal air in addition to decreased minute ventilation. Our findings suggest a role of nasal NO in sleep or in the physiologic processes accompanying sleep.

Sleep deprivation (SD) induces a rapid amelioration of mood in about 60 % of depressed patients. After the next night of sleep, however, most patients experience a relapse. Previous studies demonstrated that a six day sleep-phase advance protocol prevents relapses in about 60 % of patients who responded positively to SD. We investigated whether also a three day phase advance of the sleep period might be able to maintain the antidepressant effects of SD. Twenty-eight medicated depressed inpatients, who had a significant improvement after a SD in one night were recruited for this study. The phase advance protocol began on the first day after SD with a bed time from 5:00 p. m. to 12:00 p. m. on the first, from 7:00 p. m. to 2:00 a. m. on the second and 9:00 p. m. to 4:00 a. m. on the third day after SD. Three patients dropped out because of protocol violations. Only ten of the remaining 25 SD responders had a relapse during the three days of phase advance treatment or during the two days after it. Two of the relapsers improved again until day 6, i. e. 68 % showed an improvement of at least 30 % six days after the beginning of the treatment. This study indicates that even a three day phase advance protocol may help to prevent relapses after successful SD.

Urology clinical trials assessing bladder function have relied on the self-reported duration of the first uninterrupted sleep period (FUSP) as a proxy outcome for sleep, but the relationship between this measure and more conventional self-reported measures of sleep is unknown. In this study, we examined the association between changes in FUSP and a widely used self-reported measure of sleep, the Pittsburgh Sleep Quality Index (PSQI).We conducted post hoc (secondary) analyses of unpublished data from a previously published randomized clinical trial (NCT00477490) of desmopressin (a medication used to treat nocturia) and examined relationships between baseline and 4-week change in FUSP and PSQI global and subscale scores for participants (N = 580 to N = 606) having complete data.Data indicated strong associations between change in PSQI global score and FUSP change in six of seven subscale scores. A reduction of 1.8 points in the PSQI global score was associated with a 72-min lengthening of FUSP.Results suggest that FUSP is a potentially valuable metric that correlates with changes in perceived sleep duration, depth, quality for the entire night, efficiency, latency, and daytime function. An increase in FUSP was related to improvement in nearly all PSQI subscales. The validity of this measure in the general population remains to be determined.

Previous studies have inferred a relationship between core temperature and sleep disruption from manipulations of core temperature such as heating prior to sleep or administration of hyperthermic substances. To examine the relationship more directly, this study aimed to produce a direct increase in core temperature during the sleep period. Following an adaptation night, 16 subjects underwent counter-balanced baseline and experimental conditions, on non-consecutive nights between 1900 and 0800h. In the experimental condition, subjects were heated between 0230h and wake up, which significantly increased mean core temperature from baseline levels between 0400 and 0700h by 0.18 +/- 0.03 degree C (mean +/- SEM, p < 0.05). This increase in core temperature was associated with a significant decrease in sleep efficiency between 0330 and 0730h of 5.5 +/- 0.9% (mean +/- SD, p < 0.05). Polysomnographic measures indicated a significant increase in the number of stage changes and the amounts of stage 0 and stage 1 sleep (p < 0.05). Other stages of sleep and the number and duration of arousals were not significantly effected by heating. There was a strong trend toward and increase in the number of arousals (p = 0.054), however, core body temperature did not increase across arousals. Also, melatonin output was not effected by heating. Taken together, these results suggest that increased nocturnal core temperature alone may disrupt sleep. Additionally, the results support evidence suggesting that the circadian regulation of the sleep/wake cycle may be mediated via core temperature.

The sleep of 52 healthy paid subjects (23 male) divided into three age-bands (20-34, 35-49 and 50-70 y) were recorded at night in their homes for a total of 190 subject-nights while following their normal daily activities and habitual sleep-wake schedule. There was a shortening in both nocturnal total sleep period and total sleep time (TST) with age, the oldest group sleeping 46 min less than the youngest. Also, the mid-point of sleep occurred 32 min earlier in the oldest group compared with the youngest group. The reduction in TST with age was due, in part, to increased wake periods within sleep. The youngest subjects showed more Movement Time which progressively decreased with age while the amount of stage 1 increased with age. The amount of slow-wave sleep (SWS, stages 3+4) was reduced, stage 4 was more than halved, while REM was slightly reduced with age. There were far fewer significant gender differences in the sleep variables: males, particularly in the middle and oldest age bands, had more stage 1 than females, while females had more SWS, particularly stage 3, than males. In general, despite relatively limited subject selection criteria, there was good agreement with previous laboratory-based normative sleep values for the effect of age and gender.

The purpose of this work was to describe the basic statistical properties of the process of production of movements measured with a wrist actimeter, along a complete sleep period in normal human subjects. Two distinct types of random magnitudes were considered to analyze the data, the times between successive groups of movements and the number of movements at each fixed time (1 min) measurement epoch. Suitable probabilistic models for the two variates were chosen, fitting theoretical distribution functions to the observed data. It is concluded that interval data fit a one-parameter exponential distribution, while the number of movements fit a two-parameter negative binomial distribution. The estimated values of these parameters, besides being necessary to perform further statistical analysis, are a measure of the intensity and frequency of the movements. Finally the relationship between polysomnography measures and the elicited parameters was studied.

The aim of this work is the creation of a completely automatic method for the extraction of informative parameters from peripheral signals recorded through a sensorized T-shirt. The acquired data belong to patients affected from bipolar disorder, and consist of RR series, body movements and activity type. The extracted features, i.e. linear and non-linear HRV parameters in the time domain, HRV parameters in the frequency domain, and parameters indicative of the sleep quality, profile and fragmentation, are of interest for the automatic classification of the clinical mood state. The analysis of this dataset, which is to be performed online and automatically, must address the problems related to the clinical protocol, which also includes a segment of recording in which the patient is awake, and to the nature of the device, which can be sensitive to movements and misplacement. Thus, the decision tree implemented in this study performs the detection and isolation of the sleep period, the elimination of corrupted recording segments and the checking of the minimum requirements of the signals for every parameter to be calculated.

Bright light in the blue-green range, administered in the early morning hours (prior to waking) may be particularly effective in shifting circadian rhythms and may increase gonadotropin production. Accordingly, we tested the feasibility and utility of a mask that emits bright blue/green light (compared to a similar mask that emitted a dim red light) towards the end of sleep in a randomized, placebocontrolled pilot study. The study included a three-day baseline period, immediately followed by a 12-day intervention period. Subjects were 30 healthy young men with minimal-mild depression. The bright light masks were welltolerated and demonstrated adequate safety and feasibility. Following the intervention, those who wore the bright light mask demonstrated altered sleep timing suggestive of an earlier sleep period, and excreted a slight increase in follicle-stimulating hormone (FSH). Overall, light masks may prove useful in future studies of bright light therapy. Copyright © 2013 Taylor & Francis.

Nocturnal core temperature fall was significantly inhibited by green, blue, and red light exposure with 1,000 lx from 21:00 h to 02:00 h. The core temperature in red became identical from that in control during the following sleep period, but not in green and blue. These findings are discussed in terms of urinary melatonin behavior.

Memory representations are reactivated during slow-wave sleep (SWS) after learning, and these reactivations cause a beneficial effect of sleep for memory consolidation. Memory reactivations can also be externally triggered during sleep by associated cues which enhance the sleep-dependent memory consolidation process. Here, we compared in humans the influence of sleep periods (i) of 40 min and (ii) of 90 min without externally triggered reactivations and (iii) of externally triggered reactivations by an associated odor cue during a 40-min sleep period on the consolidation of previously learned hippocampus-dependent visuo-spatial memories. We show that external reactivation by an odor cue during the 40-min sleep period enhanced memory stability to the same extent as 90 min of sleep without odor reactivation. In contrast, 40 min of sleep without external reactivations were not sufficient to benefit memory. In the 90-min sleep condition, memory enhancements were associated with time spent in SWS and were independent of the presence or absence of REM sleep. These results suggest that the efficacy of hippocampus-dependent memory consolidation depends on the duration of sleep and particularly SWS. External reactivation cues can accelerate the consolidation process even during shorter sleep episodes.