Noise-induced sleep disruption from wind turbines: scientific updates and acoustical standards.

Wind energy appears to place global environmental benefits against local human health, particularly sleep. The result is a significant challenge to wind-energy development for the achievement of large-scale alternative energy. Our purpose is to examine noise from wind turbines and its potential to disrupt sleep, to examine the human health literature addressing these concerns, and to provide insight into how developers and communities can employ these concepts to pursue wind energy without impacting human health. The latest and most rigorous research on noise from wind turbines points to healthy sleep, when turbines are sited reasonably. This includes audible noise, low-frequency noise, and infrasound. Recent advances in acoustical standards provide practical methods to ensure adherence to these scientific findings. There now exist key data concerning wind-turbine noise, and its impact on sleep. Knowing that information, and how to deploy it with modern engineering standards should simultaneously facilitate wind development and protect human health.

Head Motion Predicts Transient Loss of Consciousness in Human Head Trauma: A Case-Control Study of Mixed Martial Artists.

OBJECTIVE: Concussion with transient loss of consciousness is a commonly observed but poorly understood phenomenon with mounting clinical significance. This study aimed to examine the relationship between head motion in varying planes and transient loss of consciousness in athletes with brain injuries. STUDY DESIGN: A case-control design was used. The Ultimate Fighting Championship database was screened for events ending with knockouts from 2013 to 2016. Time of strike, striking implement, strike location, and head motion were recorded for all knockout strikes (cases) and for a subset of nonknockout strikes (controls). Characteristics of winners and losers were compared using two-tailed t tests. Multivariate logistic regression was used to determine odds ratios for strike characteristics associated with transient loss of consciousness. The Kaplan-Meier estimate was used to describe the temporal distribution of knockouts. RESULTS: One hundred thirty-six fights were identified and 110 videos were included. Head motion in the axial plane was strongly associated with transient loss of consciousness (odds ratio, 45.3; 95% confidence interval, 20.8-98.6). Other predictors of transient loss of consciousness were head motion in sagittal and coronal planes, nonfist striking implements, and strikes to the mandible or maxilla. The Kaplan-Meier survival curve demonstrated a decreasing rate of knockouts through time. CONCLUSIONS: Rotational head acceleration, particularly in the axial plane, is strongly associated with transient loss of consciousness.

Sleep deficiency and motor vehicle crash risk in the general population: a prospective cohort study.

BACKGROUND: Insufficient sleep duration and obstructive sleep apnea, two common causes of sleep deficiency in adults, can result in excessive sleepiness, a well-recognized cause of motor vehicle crashes, although their contribution to crash risk in the general population remains uncertain. The objective of this study was to evaluate the relation of sleep apnea, sleep duration, and excessive sleepiness to crash risk in a community-dwelling population. METHODS: This was a prospective observational cohort study nested within the Sleep Heart Health Study, a community-based study of the health consequences of sleep apnea. The participants were 1745 men and 1456 women aged 40-89 years. Sleep apnea was measured by home polysomnography and questionnaires were used to assess usual sleep duration and daytime sleepiness. A follow-up questionnaire 2 years after baseline ascertained driving habits and motor vehicle crash history. Logistic regression analysis was used to examine the relation of sleep apnea and sleep duration at baseline to the occurrence of motor vehicle crashes during the year preceding the follow-up visit, adjusting for relevant covariates. The population-attributable fraction of motor vehicle crashes was estimated from the sample proportion of motor vehicle crashes and the adjusted odds ratios for motor vehicle crash within each exposure category. RESULTS: Among 3201 evaluable participants, 222 (6.9%) reported at least one motor vehicle crash during the prior year. A higher apnea-hypopnea index (p < 0.01), fewer hours of sleep (p = 0.04), and self-reported excessive sleepiness (p < 0.01) were each significantly associated with crash risk. Severe sleep apnea was associated with a 123% increased crash risk, compared to no sleep apnea. Sleeping 6 hours per night was associated with a 33% increased crash risk, compared to sleeping 7 or 8 hours per night. These associations were present even in those who did not report excessive sleepiness. The population-attributable fraction of motor vehicle crashes was 10% due to sleep apnea and 9% due to sleep duration less than 7 hours. CONCLUSIONS: Sleep deficiency due to either sleep apnea or insufficient sleep duration is strongly associated with motor vehicle crashes in the general population, independent of self-reported excessive sleepiness.

Dexmedetomidine promotes biomimetic non-rapid eye movement stage 3 sleep in humans: A pilot study.

OBJECTIVES: Sleep, which comprises of rapid eye movement (REM) and non-REM stages 1-3 (N1-N3), is a natural occurring state of decreased arousal that is crucial for normal cardiovascular, immune and cognitive function. The principal sedative drugs produce electroencephalogram beta oscillations, which have been associated with neurocognitive dysfunction. Pharmacological induction of altered arousal states that neurophysiologically approximate natural sleep, termed biomimetic sleep, may eliminate drug-induced neurocognitive dysfunction. METHODS: We performed a prospective, single-site, three-arm, randomized-controlled, crossover polysomnography pilot study (n = 10) comparing natural, intravenous dexmedetomidine- (1-µg/kg over 10 min [n = 7] or 0.5-µg/kg over 10 min [n = 3]), and zolpidem-induced sleep in healthy volunteers. Sleep quality and psychomotor performance were assessed with polysomnography and the psychomotor vigilance test, respectively. Sleep quality questionnaires were also administered. RESULTS: We found that dexmedetomidine promoted N3 sleep in a dose dependent manner, and did not impair performance on the psychomotor vigilance test. In contrast, zolpidem extended release was associated with decreased theta (∼5-8 Hz; N2 and N3) and increased beta oscillations (∼13-25 Hz; N2 and REM). Zolpidem extended release was also associated with increased lapses on the psychomotor vigilance test. No serious adverse events occurred. CONCLUSIONS: Pharmacological induction of biomimetic N3 sleep with psychomotor sparing benefits is feasible. SIGNIFICANCE: These results suggest that α2a adrenergic agonists may be developed as a new class of sleep enhancing medications with neurocognitive sparing benefits.

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis.

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible-elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications.

Sleepiness.

Sleep medicine can be a particularly rewarding clinical area for neurologists. After all, the driving organ of sleep is the brain. Many of the sleep disorders are primary brain disorders, whereas other sleep disorders (and their medications) influence brain function. But without an organized approach, even the engaged and motivated neurologist can easily become frustrated when dealing with patients whose concerns center on an undesirable degree of sleepiness. Lost in the thicket of information provided during the patient-doctor encounter, many physicians are unable to direct the history toward particular diagnostic hypotheses. So, rather than provide an exhaustive and disorganized set of details about sleep medicine, the author instead shares pearls of sleep medicine in the context of an overall framework, with the goal to foster targeted history-taking for the successful diagnosis of a patient struggling with maintaining wakefulness. The topic of excessive sleepiness will be covered because it is so common and because its mastery is fundamental to approaching most patients with sleep disorders. Common and important pitfalls regarding the topic of sleepiness-and how to avoid them-will be discussed. Misdiagnoses and mismanagement are easy to avoid if this entire framework is kept in mind.

Tracking the sleep onset process: an empirical model of behavioral and physiological dynamics.

The sleep onset process (SOP) is a dynamic process correlated with a multitude of behavioral and physiological markers. A principled analysis of the SOP can serve as a foundation for answering questions of fundamental importance in basic neuroscience and sleep medicine. Unfortunately, current methods for analyzing the SOP fail to account for the overwhelming evidence that the wake/sleep transition is governed by continuous, dynamic physiological processes. Instead, current practices coarsely discretize sleep both in terms of state, where it is viewed as a binary (wake or sleep) process, and in time, where it is viewed as a single time point derived from subjectively scored stages in 30-second epochs, effectively eliminating SOP dynamics from the analysis. These methods also fail to integrate information from both behavioral and physiological data. It is thus imperative to resolve the mismatch between the physiological evidence and analysis methodologies. In this paper, we develop a statistically and physiologically principled dynamic framework and empirical SOP model, combining simultaneously-recorded physiological measurements with behavioral data from a novel breathing task requiring no arousing external sensory stimuli. We fit the model using data from healthy subjects, and estimate the instantaneous probability that a subject is awake during the SOP. The model successfully tracked physiological and behavioral dynamics for individual nights, and significantly outperformed the instantaneous transition models implicit in clinical definitions of sleep onset. Our framework also provides a principled means for cross-subject data alignment as a function of wake probability, allowing us to characterize and compare SOP dynamics across different populations. This analysis enabled us to quantitatively compare the EEG of subjects showing reduced alpha power with the remaining subjects at identical response probabilities. Thus, by incorporating both physiological and behavioral dynamics into our model framework, the dynamics of our analyses can finally match those observed during the SOP.

Interactions of time of day and sleep with between-session habituation and extinction memory in young adult males.

Within-session habituation and extinction learning co-occur as do subsequent consolidation of habituation (i.e., between-session habituation) and extinction memory. We sought to determine whether, as we predicted: (1) between-session habituation is greater across a night of sleep versus a day awake; (2) time-of-day accounts for differences; (3) between-session habituation predicts consolidation of extinction memory; (4) sleep predicts between-session habituation and/or extinction memory. Participants (N = 28) completed 4-5 sessions alternating between mornings and evenings over 3 successive days (2 nights) with session 1 in either the morning (N = 13) or evening (N = 15). Twelve participants underwent laboratory polysomnography. During 4 sessions, participants completed a loud-tone habituation protocol, while skin conductance response (SCR), blink startle electromyography (EMG), heart-rate acceleration and heart-rate deceleration (HRD) were recorded. For sessions 1 and 2, between-session habituation of EMG, SCR and HRD was greater across sleep. SCR and HRD were generally lower in the morning. Between-session habituation of SCR for sessions 1 and 2 was positively related to intervening (first night) slow wave sleep. In the evening before night 2, participants also underwent fear conditioning and extinction learning phases of a second protocol. Extinction recall was tested the following morning. Extinction recall was predicted only by between-session habituation of SCR across the same night (second night) and by intervening REM. We conclude that: (1) sleep augments between-session habituation, as does morning testing; (2) extinction recall is predicted by concurrent between-session habituation; and (3) both phenomena may be influenced by sleep.

The subjective-objective mismatch in sleep perception among those with insomnia and sleep apnea.

The diagnosis and management of insomnia relies primarily on clinical history. However, patient self-report of sleep-wake times may not agree with objective measurements. We hypothesized that those with shallow or fragmented sleep would under-report sleep quantity, and that this might account for some of the mismatch. We compared objective and subjective sleep-wake times for 277 patients who underwent diagnostic polysomnography. The group included those with insomnia symptoms (n = 92), obstructive sleep apnea (n = 66) or both (n = 119). Mismatch of wake duration was context dependent: all three groups overestimated sleep latency but underestimated wakefulness after sleep onset. The insomnia group underestimated total sleep time by a median of 81 min. However, contrary to our hypothesis, measures of fragmentation (N1, arousal index, sleep efficiency, etc.) did not correlate with the subjective sleep duration estimates. To unmask a potential relationship between sleep architecture and subjective duration, we tested three hypotheses: N1 is perceived as wake; sleep bouts under 10 min are perceived as wake; or N1 and N2 are perceived in a weighted fashion. None of these hypotheses exposed a match between subjective and objective sleep duration. We show only modest performance of a Naïve Bayes Classifier algorithm for predicting mismatch using clinical and polysomnographic variables. Subjective-objective mismatch is common in patients reporting insomnia symptoms. We conclude that mismatch was not attributable to commonly measured polysomnographic measures of fragmentation. Further insight is needed into the complex relationships between subjective perception of sleep and conventional, objective measurements.

The impact of body posture and sleep stages on sleep apnea severity in adults.

STUDY OBJECTIVES: Determining the presence and severity of obstructive sleep apnea (OSA) is based on apnea and hypopnea event rates per hour of sleep. Making this determination presents a diagnostic challenge, given that summary metrics do not consider certain factors that influence severity, such as body position and the composition of sleep stages. METHODS: We retrospectively analyzed 300 consecutive diagnostic PSGs performed at our center to determine the impact of body position and sleep stage on sleep apnea severity. RESULTS: The median percent of REM sleep was 16% (reduced compared to a normal value of ~25%). The median percent supine sleep was 65%. Fewer than half of PSGs contained > 10 min in each of the 4 possible combinations of REM/NREM and supine/non-supine. Half of patients had > 2-fold worsening of the apnea-hypopnea index (AHI) in REM sleep, and 60% had > 2-fold worsening of AHI while supine. Adjusting for body position had greater impact on the AHI than adjusting for reduced REM%. Misclassification--specifically underestimation of OSA severity--is attributed more commonly to body position (20% to 40%) than to sleep stage (~10%). CONCLUSIONS: Supine-dominance and REM-dominance commonly contribute to AHI underestimation in single-night PSGs. Misclassification of OSA severity can be mitigated in a patient-specific manner by appropriate consideration of these variables. The results have implications for the interpretation of single-night measurements in clinical practice, especially with trends toward home testing devices that may not measure body position or sleep stage.

Sleep disruption due to hospital noises: a prospective evaluation.

BACKGROUND: Sleep plays a critical role in maintaining health and well-being; however, patients who are hospitalized are frequently exposed to noise that can disrupt sleep. Efforts to attenuate hospital noise have been limited by incomplete information on the interaction between sounds and sleep physiology. OBJECTIVE: To determine profiles of acoustic disruption of sleep by examining the cortical (encephalographic) arousal responses during sleep to typical hospital noises by sound level and type and sleep stage. DESIGN: 3-day polysomnographic study. SETTING: Sound-attenuated sleep laboratory. PARTICIPANTS: Volunteer sample of 12 healthy participants. INTERVENTION: Baseline (sham) night followed by 2 intervention nights with controlled presentation of 14 sounds that are common in hospitals (for example, voice, intravenous alarm, phone, ice machine, outside traffic, and helicopter). The sounds were administered at calibrated, increasing decibel levels (40 to 70 dBA [decibels, adjusted for the range of normal hearing]) during specific sleep stages. MEASUREMENTS: Encephalographic arousals, by using established criteria, during rapid eye movement (REM) sleep and non-REM (NREM) sleep stages 2 and 3. RESULTS: Sound presentations yielded arousal response curves that varied because of sound level and type and sleep stage. Electronic sounds were more arousing than other sounds, including human voices, and there were large differences in responses by sound type. As expected, sounds in NREM stage 3 were less likely to cause arousals than sounds in NREM stage 2; unexpectedly, the probability of arousal to sounds presented in REM sleep varied less by sound type than when presented in NREM sleep and caused a greater and more sustained elevation of instantaneous heart rate. LIMITATIONS: The study included only 12 participants. Results for these healthy persons may underestimate the effects of noise on sleep in patients who are hospitalized. CONCLUSION: Sounds during sleep influence both cortical brain activity and cardiovascular function. This study systematically quantifies the disruptive capacity of a range of hospital sounds on sleep, providing evidence that is essential to improving the acoustic environments of new and existing health care facilities to enable the highest quality of care. PRIMARY FUNDING SOURCE: Academy of Architecture for Health, Facilities Guidelines Institute, and The Center for Health Design.

Memory for semantically related and unrelated declarative information: the benefit of sleep, the cost of wake.

Numerous studies have examined sleep's influence on a range of hippocampus-dependent declarative memory tasks, from text learning to spatial navigation. In this study, we examined the impact of sleep, wake, and time-of-day influences on the processing of declarative information with strong semantic links (semantically related word pairs) and information requiring the formation of novel associations (unrelated word pairs). Participants encoded a set of related or unrelated word pairs at either 9 am or 9 pm, and were then tested after an interval of 30 min, 12 hr, or 24 hr. The time of day at which subjects were trained had no effect on training performance or initial memory of either word pair type. At 12 hr retest, memory overall was superior following a night of sleep compared to a day of wakefulness. However, this performance difference was a result of a pronounced deterioration in memory for unrelated word pairs across wake; there was no sleep-wake difference for related word pairs. At 24 hr retest, with all subjects having received both a full night of sleep and a full day of wakefulness, we found that memory was superior when sleep occurred shortly after learning rather than following a full day of wakefulness. Lastly, we present evidence that the rate of deterioration across wakefulness was significantly diminished when a night of sleep preceded the wake period compared to when no sleep preceded wake, suggesting that sleep served to stabilize the memories against the deleterious effects of subsequent wakefulness. Overall, our results demonstrate that 1) the impact of 12 hr of waking interference on memory retention is strongly determined by word-pair type, 2) sleep is most beneficial to memory 24 hr later if it occurs shortly after learning, and 3) sleep does in fact stabilize declarative memories, diminishing the negative impact of subsequent wakefulness.

DiBa: a data-driven Bayesian algorithm for sleep spindle detection.

Although the spontaneous brain rhythms of sleep have commanded much recent interest, their detection and analysis remains suboptimal. In this paper, we develop a data-driven Bayesian algorithm for sleep spindle detection on the electroencephalography (EEG). The algorithm exploits the Karhunen-Loève transform and Bayesian hypothesis testing to produce the instantaneous probability of a spindle's presence with maximal resolution. In addition to possessing flexibility, transparency, and scalability, this algorithm could perform at levels superior to standard methods for EEG event detection.

Drug-induced sleep: theoretical and practical considerations.

Faithful replication of normal sleep through medications--can it be achieved? Departure from normal sleep with the use of drugs--when is it desired? Answers to these questions depend on accurate understanding of sleep and on concrete criteria upon which to define it. Since these elements are evolving sciences, as yet incompletely known, one might take a nihilistic approach that we simply cannot judge whether we have successfully replicated sleep, since we do not fully grasp what sleep is or what it does. To address these potential obstacles, our article is written in two sections. The first addresses theoretical considerations for how medications might be seen in the larger framework of sleep. The purpose of this section is to inform readers about key issues in evaluating whether a drug has sufficient data to persuasively argue it is re-creating sleep. (We hope that researchers interested in conducting studies, or critical readers of the drug-study literature, might find this section particularly useful.) The second section of this article approaches exemplary, current concepts of pharmacologic manipulation of sleep, organized by disorders as articulated by the International Classification of Sleep Disorders (2005). This second section will combine practical knowledge of clinical sleep medicine, with emphasis on contemporary knowledge about molecular mechanisms that are felt to underlie some of these phenomena. We recognize that our collective knowledge about sleep will advance in the coming years. We hope that this article serves to facilitate that advance.