Sleep Stages Research Articles

Daytime dexmedetomidine sedation with closed-loop acoustic stimulation alters slow wave sleep homeostasis in healthy adults

BackgroundThe alpha-2 adrenergic agonist dexmedetomidine induces EEG patterns resembling those of non-rapid eye movement (NREM) sleep. Fulfilment of slow wave sleep (SWS) homeostatic needs would address the assumption that dexmedetomidine induces functional biomimetic sleep states. MethodsIn-home sleep EEG recordings were obtained from 13 healthy participants before and after dexmedetomidine sedation. Dexmedetomidine target-controlled infusions and closed-loop acoustic stimulation were implemented to induce and enhance EEG slow waves, respectively. EEG recordings during sedation and sleep were staged using modified American Academy of Sleep Medicine criteria. Slow wave activity (EEG power from 0.5 to 4 Hz) was computed for NREM stage 2 (N2) and NREM stage 3 (N3/SWS) epochs, with the aggregate partitioned into quintiles by time. The first slow wave activity quintile served as a surrogate for slow wave pressure, and the difference between the first and fifth quintiles as a measure of slow wave pressure dissipation. ResultsCompared with pre-sedation sleep, post-sedation sleep showed reduced N3 duration (mean difference of −17.1 min, 95% confidence interval −30.0 to −8.2, P=0.015). Dissipation of slow wave pressure was reduced (P=0.02). Changes in combined durations of N2 and N3 between pre- and post-sedation sleep correlated with total dexmedetomidine dose, (r=−0.61, P=0.03). ConclusionsDaytime dexmedetomidine sedation and closed-loop acoustic stimulation targeting EEG slow waves reduced N3/SWS duration and measures of slow wave pressure dissipation on the post-sedation night in healthy young adults. Thus, the paired intervention induces sleep-like states that fulfil certain homeostatic NREM sleep needs in healthy young adults. Clinical trial registrationClinicalTrials.gov NCT04206059.

The Effectiveness of Hammock Positioning in Regulating Behavioral Patterns in Preterm: A Systematic Review

Background- Preterm newborns benefit from supportive developmental techniques such as hammock placement, which give them a sense of being in the womb that promotes calm, relaxation, and deep restful sleep. Objective- To identify and synthesize the available evidence on the effect of hammock positioning in regulating behavioral patterns and sleep in preterm infants admitted to the NICU Data Sources: We searched the Google Scholar, Pubmed, and Scopus databases for reports of primary research studies using a three-step strategy. We also searched for and reviewed the reference lists of retrieved articles. Methods: We included data from randomized controlled trials, Quasi-experimental and Comparative study measuring the effects of hammock positioning on physiological stress outcomes, defined as oxygen saturation, body temperature, heart rate and respiratory rate, Sleep-wakefulness, and behavioral pattern. The PRISMA model was used to conduct data extraction. We performed a narrative synthesis of all studies when data were available from multiple studies. Results: Five studies were eligible for inclusion. Infants who received hammock positioning has shown to have a higher mean heart rate, oxygen saturation and temperature, Sleep-wakefulness and improved behavioral patterns. Conclusions: Current evidence suggests that hammock positioning in the neonatal intensive care unit setting is a safe method that may significantly affect some of the physiological parameters of stress, improved behavioral patterns and Sleep-wakefulness in preterm infants. However, due to clinical heterogeneity, further studies are needed to assess the effects of physiological stress in the neonatal intensive care unit on the development of preterm infants.

Does Targeted Memory Reactivation during SWS and REM sleep have differential effects on mnemonic discrimination and generalization?

Targeted memory reactivation (TMR), or the presentation of learning-related cues during sleep, has been shown to benefit memory consolidation for specific memory traces when applied during non-rapid eye movement (NREM) sleep. Prior studies suggest that TMR during REM sleep may play a role in memory generalization processes, but evidence remains scarce. We tested the hypothesis that TMR exerts a differential effect on distinct mnemonic processes as a function of the sleep state (REM vs. NREM) in which TMR is delivered. Mnemonic discrimination and generalization of semantic categories were investigated using an adapted version of the Mnemonic Similarity Task, before and after sleep. Forty-eight participants encoded pictures from eight semantic categories, each associated with a sound. In the pre-sleep immediate test, they had to discriminate "old" (targets) from "similar" (lures) or "new" (foils) pictures. During sleep, half of the sounds were replayed in slow wave sleep (SWS) or REM sleep. Recognition, discrimination, and generalization memory indices were tested in the morning. These indices did not differ between SWS and REM TMR groups or reactivated and non-reactivated item categories. Additional results suggest a positive effect of TMR on performance for highly similar items mostly relying on mnemonic discrimination processes. During sleep, EEG activity after cue presentation increased in the delta-theta and sigma band in the SWS group, and in the beta band in the REM TMR group. These results do not support the hypothesis of a differential processing of novel memory traces when TMR is administered in distinctive physiological sleep states.

Targeted memory reactivation during non-rapid eye movement sleep enhances neutral, but not negative, components of memory.

Emotionally salient components of memory are preferentially remembered at the expense of accompanying neutral information. This emotional memory trade-off is enhanced over time, and possibly sleep, through a process of memory consolidation. Sleep is believed to benefit memory through a process of reactivation during non-rapid eye movement sleep (NREM). Here, targeted memory reactivation (TMR) was used to manipulate the reactivation of negative and neutral memories during NREM sleep. Thirty-one male and female participants encoded composite scenes containing either a negative or neutral object superimposed on an always neutral background. During NREM sleep, sounds associated with the scene object were replayed, and memory for object and background components was tested the following morning. We found that TMR during NREM sleep improved memory for neutral, but not negative scene objects. This effect was associated with sleep spindle activity, with a larger spindle response following TMR cues predicting TMR effectiveness for neutral items only. These findings therefore do not suggest a role of NREM memory reactivation in enhancing the emotional memory trade-off across a 12-hour period but do align with growing evidence of spindle-mediated memory reactivation in service of neutral declarative memory.Significance statement Memory reactivation during sleep is believed to be a key mechanism facilitating consolidation, the strengthening and stabilisation of memories over time. Emotional memories appear to be preferentially consolidated compared to neutral information, but the role sleep-related memory reactivation in this process is still unclear. Here, we found that experimentally reactivating memories during sleep in humans did not preferentially enhance emotional memory components but did improve neutral memory when tested after one night of sleep. These findings speak against a role of memory reactivation in the early stages of emotional memory consolidation.

Thalamocortical dynamics during Rapid Eye Movement Sleep in the Mouse Somatosensory Pathway.

Rapid eye movement sleep (REM), also referred to as paradoxical sleep for the striking resemblance of its electroencephalogram (EEG) to the one observed in wakefulness, is characterized by the occurrence of transient events such as limb twitches or facial and rapid eye movements. Here, we investigated the local activity of the primary somatosensory or barrel cortex (S1) in naturally sleeping head-fixed male mice during REM. Through local field potential (LFP) recordings, we uncovered local appearances of spindle waves in the barrel cortex during REM concomitant with strong delta power, challenging the view of a wakefulness-like activity in REM. We further performed extra- and intracellular recordings of thalamic cells in head-fixed mice. Our data show high frequency thalamic bursts of spikes and subthreshold spindle oscillations in about half of the neurons of the ventral posterior medial nucleus which further confirmed the thalamic origin of local cortical spindles in S1 in REM. Cortical spindle oscillations were suppressed, while thalamus spike firing increased, associated with rapid mouse whisker movements and S1 cortical activity transitioned to an activated state. During REM, sensory thalamus and barrel cortex therefore alternate between high (wake-like) and low (non-REM sleep-like) activation states, potentially providing a neuronal substrate for mnemonic processes occurring during this paradoxical sleep stage.Significance Statement Mammalian sleep includes slow wave sleep, or non-rapid eye movement sleep (NREM), and the subsequent REM sleep (REM). At the EEG global level, cortical activity during REM sleep has long been believed to share some similarities with awake cortical activity. The well-defined mouse whisker system offers the unique opportunity to precisely investigate cortical and thalamic dynamics during wakefulness and REM. Combining local field potential (LFP) recordings in primary somatosensory cortex, with single-unit neuronal recordings in its associated thalamic nucleus, we found that during REM, sensory thalamus and barrel cortex alternate between high (wake-like) and low (non-REM sleep-like) activation states, potentially providing a neuronal substrate for mnemonic processes occurring during this paradoxical sleep stage.

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. We developed a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry. After exclusion, 1448 participant nights of data were used for training. The difference between polysomnography and the model classifications on the external validation was 34.7 min (95% limits of agreement (LoA): −37.8–107.2 min) for total sleep duration, 2.6 min for REM duration (95% LoA: −68.4–73.4 min) and 32.1 min (95% LoA: −54.4–118.5 min) for NREM duration. The sleep classifier was deployed in the UK Biobank with 100,000 participants to study the association of sleep duration and sleep efficiency with all-cause mortality. Among 66,214 UK Biobank participants, 1642 mortality events were observed. Short sleepers (<6 h) had a higher risk of mortality compared to participants with normal sleep duration of 6–7.9 h, regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.58; 95% confidence intervals (CIs): 1.19–2.11) or high sleep efficiency (HRs: 1.45; 95% CIs: 1.16–1.81). Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

Large Muscle Group Movements during Sleep in Restless Leg Syndrome: Neurophysiological and Clinical Implications.

Recently, criteria have been drawn up for Large Muscle group Movements during sleep (LMM), defined as movements lasting for 3-45 seconds in adults, which are often accompanied by changes in sleep stage, arousals, and increases in heart rate. The aim of this study was to characterize LMM in RLS, in order to better evaluate their impact on the neurophysiology of the disorder and, therefore, the possible clinical implications. Consecutive, drug-free patients diagnosed with RLS and controls, aged 18 years or more, were retrospectively enrolled. Leg movement activity - short-interval (SILMS), periodic (PLMS) and isolated (ISOLMS) leg movements during sleep - and LMM were detected and scored. One-hundred patients and 67 controls were recruited. All movement measures were significantly higher in RLS. A significant positive correlation was found between LMM and ISOLMS index but not PLMS index in both groups. LMM index showed a significant negative correlation with total sleep time, sleep efficiency, and percentage of sleep stages N3 and R, as well as a significant positive correlation with number of awakenings, and percentage of sleep stages N1 and N2 only in patients with RLS. No significant correlation was found for either LMM or PLMS index and RLS severity. Different types of movements, including SILMS, ISOLMS, and LMM, play somewhat distinct roles in sleep neurophysiology in RLS. Notably, LMM, a newly recognized category of movements, demonstrate associations with sleep architecture instability and fragmentation, arousals, and awakenings, suggesting potential clinical implications.

Overcoming traps and pitfalls leading to misinterpretation of normal EEG variants and variation of the background activity.

Normal EEG variants, especially the epileptiform variants, can be challenging to interpret because they often have sharp contours and may be confused with "epileptic" interictal activities. However, they can be recognized by the fact that "most spikes or sharp wave discharges of clinical import are followed by a slow wave or a series of slow deflections" (Maulsby, 1971).If there is no wave after the spike, electroencephalographers should be suspicious of artifacts and normal EEG variants. Most normal EEG variants display a single rhythm with the same frequency within the pattern and the morphology remains stable throughout the entire EEG recording with repetition of the same pattern. In case of doubt or difficulties with a standard EEG, it is recommended to undergo an EEG that includes sleep stages with or without sleep deprivation. Finally, epileptiform is an ambiguous term corresponding to an electroencephalographic trait. Epileptiform does not imply a pathological condition, including epilepsy. The clinical context remains the most paramount in the diagnosis of epilepsy. In this article, we propose a set of rules and guidelines to identify normal EEG variants in EEG tracings and normal variation of the background activity. It is not easy to accurately assign a specific/precise name to all EEG activity, but with an orderly approach to EEG that involves using a set of criteria, nonepileptic activity can be identified.

The clinical characteristic of catathrenia: a new look at an old issue-a systematic review of existing literature.

The International Classification of Sleep Disorders categorized catathrenia as a respiratory disorder, but there are doubts whether episodes appear during rapid eye movement (REM) sleep or the non-rapid eye movement (NREM), their duration, and symptoms. The main objectives were to identify the most common features and relations of catathrenia. PubMed, Embase, and Web of Science were searched according to the PRISMA 2020 guidelines. The Joanna Briggs Institute and the ROBINS-I tools were chosen to assess the risk of bias. A total of 288 records were identified, 31 articles were included. The majority of the studies had a moderate risk of bias. 49.57% of episodes occurred during the NREM sleep, while 46% took place during REM. In 60.34% females, catathrenia was more common in the NREM, while in 59.26% of males was in REM sleep (p < 0.05). Females and obese individuals were found to have shorter episodes (p < 0.05). Age was inversely correlated with minimal episodes duration (r = - 0.34). The continuous positive airway pressure (CPAP) therapy was inversely correlated with the maximal episode duration (r = - 0.48). Catathrenia occurs with similar frequency in both genders. The most frequent symptoms embraced groaning, awareness of disturbing bedpartners, and daytime somnolence-not confirmed by the Epworth Sleepiness Scale. The episodes occur more frequently in NREM than in REM sleep. Catathrenia may be considered as a sex-specific condition. The effects of CPAP treatment leading to shortening episodes duration, which may indicate the respiratory origin of catathrenia.

5-MeO-DMT induces sleep-like LFP spectral signatures in the hippocampus and prefrontal cortex of awake rats

5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) is a potent classical psychedelic known to induce changes in locomotion, behaviour, and sleep in rodents. However, there is limited knowledge regarding its acute neurophysiological effects. Local field potentials (LFPs) are commonly used as a proxy for neural activity, but previous studies investigating psychedelics have been hindered by confounding effects of behavioural changes and anaesthesia, which alter these signals. To address this gap, we investigated acute LFP changes in the hippocampus (HP) and medial prefrontal cortex (mPFC) of freely behaving rats, following 5-MeO-DMT administration. 5-MeO-DMT led to an increase of delta power and a decrease of theta power in the HP LFPs, which could not be accounted for by changes in locomotion. Furthermore, we observed a dose-dependent reduction in slow (20–50 Hz) and mid (50–100 Hz) gamma power, as well as in theta phase modulation, even after controlling for the effects of speed and theta power. State map analysis of the spectral profile of waking behaviour induced by 5-MeO-DMT revealed similarities to electrophysiological states observed during slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. Our findings suggest that the psychoactive effects of classical psychedelics are associated with the integration of waking behaviours with sleep-like spectral patterns in LFPs.

Safety and Efficacy of AlphaWave® L-Theanine Supplementation for 28Days in Healthy Adults with Moderate Stress: A Randomized, Double-Blind, Placebo-Controlled Trial.

Prolonged periods of stress may lead to negative health consequences. AlphaWave® L-Theanine was safe and efficacious during an acute stress challenge. However, double-blind, placebo-controlled clinical trials investigating the longer term effects of L-theanine supplementation on stress are warranted. Thirty healthy adults (18-65years) with moderate stress were randomized to AlphaWave® L-Theanine (400mg L-theanine/day) or placebo (n = 15/group) for 28days. Stress was assessed by salivary cortisol, Perceived Stress Scale (PSS) and Depression, Anxiety and Stress Scale-21; sleep was assessed by the Healthy People Sleep Quality Index and actigraphy device; cognition was assessed by Computerized Mental Performance Assessment System; mood was assessed by Profile of Mood States. All outcomes were measured at baseline, Days 14 and 28. Safety included vital signs, clinical chemistry, haematology and adverse events (AEs). All AEs were resolved by the end of the study period or upon subsequent follow up, and out of range laboratory values and changes in vital signs were deemed not clinically relevant following AlphaWave® L-Theanine supplementation. Participants supplemented with AlphaWave® L-Theanine had decreases of 12.92% (p = 0.051) and 17.98% (p = 0.04) in PSS scores after 14 and 28days, respectively, while those on placebo had respective decreases of 9.74% (p = 0.061) and 17.88% (p = 0.009). There were no significant differences between groups for change in salivary cortisol. The AlphaWave® L-Theanine group demonstrated decreased time asleep after 28days and significantly reduced light sleep after 14 and 28days compared to placebo (p ≤ 0.040). The AlphaWave® L-Theanine group significantly improved by 21.79% and 21.33% in Stroop test correct reaction time after 14 and 28days, respectively, while those on placebo improved after 28days only (p = 0.005). AlphaWave® L-Theanine supplementation for 28days was safe and significantly decreased perceived stress significantly decreased perceived stress and light sleep, improved sleep quality and enhanced cognitive attention in the studied population. Larger, randomized controlled trials with longer duration of AlphaWave® L-Theanine supplementation are warranted to reduce inter-individual variability and the potential placebo effect. ClinicalTrials.gov identifier, NCT05808595.

Neuronal PAS domain 1 identifies a major subpopulation of wakefulness-promoting GABAergic neurons in the basal forebrain

Here, we describe a group of basal forebrain (BF) neurons expressing neuronal Per-Arnt-Sim (PAS) domain 1 (Npas1), a developmental transcription factor linked to neuropsychiatric disorders. Immunohistochemical staining in Npas1-cre-2A-TdTomato mice revealed BF Npas1+ neurons are distinct from well-studied parvalbumin or cholinergic neurons. Npas1 staining in GAD67-GFP knock-in mice confirmed that the vast majority of Npas1+ neurons are GABAergic, with minimal colocalization with glutamatergic neurons in vGlut1-cre-tdTomato or vGlut2-cre-tdTomato mice. The density of Npas1+ neurons was high, five to six times that of neighboring cholinergic, parvalbumin, or glutamatergic neurons. Anterograde tracing identified prominent projections of BF Npas1+ neurons to brain regions involved in sleep-wake control, motivated behaviors, and olfaction such as the lateral hypothalamus, lateral habenula, nucleus accumbens shell, ventral tegmental area, and olfactory bulb. Chemogenetic activation of BF Npas1+ neurons in the light period increased the amount of wakefulness and the latency to sleep for 2 to 3 h, due to an increase in long wake bouts and short NREM sleep bouts. NREM slow-wave and sigma power, as well as sleep spindle density, amplitude, and duration, were reduced, reminiscent of findings in several neuropsychiatric disorders. Together with previous findings implicating BF Npas1+ neurons in stress responsiveness, the anatomical projections of BF Npas1+ neurons and the effect of activating them suggest a possible role for BF Npas1+ neurons in motivationally driven wakefulness and stress-induced insomnia. Identification of this major subpopulation of BF GABAergic neurons will facilitate studies of their role in sleep disorders, dementia, and other neuropsychiatric conditions involving BF.

Multi-night acoustic stimulation is associated with better sleep, amyloid dynamics, and memory in older adults with cognitive impairment.

Sleep is a potential early, modifiable risk factor for cognitive decline and dementia. Impaired slow wave sleep (SWS) is pronounced in individuals with cognitive impairment (CI). Cognitive decline and impairments of SWS are bi-directionally linked in a vicious cycle. SWS can be enhanced non-invasively using phase-locked acoustic stimulation (PLAS), potentially breaking this vicious cycle. Eighteen healthy older adults (HC, agemean±sd, 68.3 ± 5.1) and 16 older adults (agemean±sd, 71.9 ± 3.9) with CI (Montreal Cognitive Assessment ≤ 25) underwent one baseline (sham-PLAS) night and three consecutive stimulation nights (real-PLAS). EEG responses and blood-plasma amyloid beta Aβ42/Aβ40 ratio were measured pre- and post-intervention, as was episodic memory. The latter was again evaluated 1week and 3months after the intervention. In both groups, PLAS induced a significant electrophysiological response in both voltage- and time-frequency analyses, and memory performance improved in association with the magnitude of this response. In the CI group, both electrophysiological and associated memory effects were delayed compared to the healthy group. After 3 intervention nights, electrophysiological response to PLAS was no longer different between CI and HC groups. Only in the CI sample, stronger electrophysiological responses were significantly associated with improving post-intervention Aβ42/Aβ40 ratios. PLAS seems to improve SWS electrophysiology, memory, and amyloid dynamics in older adults with CI. However, effects on memory require more time to unfold compared to healthy older adults. This indicates that PLAS may become a potential tool to ameliorate cognitive decline, but longer interventions are necessary to compensate for declining brain integrity. This study was pre-registered (clinicaltrials.gov: NCT04277104).

Selective Enhancement of REM Sleep in Male Rats through Activation of MT1 Receptors Located in the Locus Coeruleus Norepinephrine neurons.

Sleep disorders affect millions of people around the world and have a high comorbidity with psychiatric disorders. While current hypnotics mostly increase non-rapid eye movement sleep (NREMS), drugs acting selectively on enhancing rapid eye movement sleep (REMS) are lacking. This polysomnographic study in male rats showed that the first-in-class selective melatonin MT1 receptor partial agonist UCM871 increases the duration of REMs without affecting that of NREMS. The REMS-promoting effects of UCM871 occurred by inhibiting, in a dose-response manner, the firing activity of the locus coeruleus (LC) norepinephrine (NE) neurons, which express MT1 receptors. The increase of REMS duration and the inhibition of LC-NE neuronal activity by UCM871 were abolished by MT1 pharmacological antagonism and by an adeno-associated viral (AAV) vector which selectively knocked down MT1 receptors in the LC-NE neurons. In conclusion, MT1 receptor agonism inhibits LC-NE neurons and triggers REMS, thus representing a novel mechanism and target for REMS disorders and/or psychiatric disorders associated with REMS impairments.Significance Statement Rapid eye movement sleep (REMS) is involved in the processes of memory consolidation and emotional regulation, but drugs selectively enhancing REMS are scant. Herein, we show that the first-in-class selective melatonin MT1 receptor agonist UCM871, by inhibiting the activity of norepinephrine neurons in the locus coeruleus, an important nucleus regulating the sleep/wake cycle, selectively increases the duration of REMS. These findings enhance our current understanding of the neurobiology and pharmacology of REMS and provide a possible novel mechanism and target for disorders associated with REMS dysfunctions.

Sleep, Sleepiness, and Memory

Abstract Objective To evaluate the relationship between sleep and sleepiness with memory complaints. Materials and Methods Patients who were submitted to polysomnography between May and September of 2022 and answered the prospective and retrospective memory questionnaire and the Epworth sleepiness scale were included, respectively. Data were entered into an Excel spreadsheet and converted to a file compatible with the SPSS software. Results The sample consisted of 98 subjects, 62.2% male, mean age of 45.9 years, 73.4% overweight, 54.1% with comorbidities, and 51% with excessive sleepiness. There was a significant difference in sleep efficiency, respiratory disturbance index (RDI), slow wave sleep (SWS), and rapid eye movement (REM) sleep for the group with comorbidities; in latency to sleep and SWS between genders; and in RDI for the body mass index group. No correlation between RDI and memory could be identified, but there were statistically significant correlations between REM and sleep efficiency; RDI and REM sleep; RDI and SWS; SWS and sleep efficiency; and sleep efficiency and latency to sleep onset. Older adults performed better on memory tests when total sleep time (TST) is longer than 5 hours and excessive daytime sleepiness is related to complaints of prospective, retrospective, and total memory. Conclusion Elderly people with TST longer than 5 hours have a better memory. Although a correlation between RDI and memory was not observed, a correlation between excessive daytime sleepiness—one of the main symptoms of patients with sleep disorders—and memory was.

EarSleep: In-ear Acoustic-based Physical and Physiological Activity Recognition for Sleep Stage Detection

Since sleep plays an important role in people's daily lives, sleep monitoring has attracted the attention of many researchers. Physical and physiological activities occurring in sleep exhibit unique patterns in different sleep stages. It indicates that recognizing a wide range of sleep activities (events) can provide more fine-grained information for sleep stage detection. However, most of the prior works are designed to capture limited sleep events and coarse-grained information, which cannot meet the needs of fine-grained sleep monitoring. In our work, we leverage ubiquitous in-ear microphones on sleep earbuds to design a sleep monitoring system, named EarSleep1, which interprets in-ear body sounds induced by various representative sleep events into sleep stages. Based on differences among physical occurrence mechanisms of sleep activities, EarSleep extracts unique acoustic response patterns from in-ear body sounds to recognize a wide range of sleep events, including body movements, sound activities, heartbeat, and respiration. With the help of sleep medicine knowledge, interpretable acoustic features are derived from these representative sleep activities. EarSleep leverages a carefully designed deep learning model to establish the complex correlation between acoustic features and sleep stages. We conduct extensive experiments with 48 nights of 18 participants over three months to validate the performance of our system. The experimental results show that our system can accurately detect a rich set of sleep activities. Furthermore, in terms of sleep stage detection, EarSleep outperforms state-of-the-art solutions by 7.12% and 9.32% in average precision and average recall, respectively.

Respiration-triggered olfactory stimulation reduces obstructive sleep apnea severity: A prospective pilot study.

Obstructive sleep apnea is a prevalent sleep-disordered breathing condition characterized by repetitive reduction in breathing during sleep. The current care standard for obstructive sleep apnea is continuous positive air pressure devices, often suffering from low tolerance due to limited adherence. Capitalizing on the unique neurocircuitry of olfactory perception and its retained function during sleep, we conducted a pilot study to test transient, respiration-based olfactory stimulation as a treatment for obstructive sleep apnea markers. Thirty-two patients with obstructive sleep apnea (apnea-hypopnea index ≥ 15 events per hr) underwent two polysomnography sessions, "Odour" and "Control", in random order. In "Odour" nights, patients were presented with transient respiratory-based olfactory stimulation delivered via a computer-controlled commercial olfactometer (Scentific). The olfactometer, equipped with a wireless monitoring, analysed respiratory patterns and presented odour upon detection of respiratory events. No odours were presented in "Control" nights. Following exclusions, 17 patients entered the analysis (four women, 47.4 (10.5) years, body mass index: 29.4 (6.3) kg m-2). We observed that olfactory stimulation during sleep reduced the apnea-hypopnea index ("Odour": 17.2 (20.9), "Control": 28.2 (18.6), z = -3.337, p = 0.000846, BF10 [Bayesian Factor 10]= 57.9), reflecting an average decrease of 31.3% in the number of events. Relatedly, stimulation reduced the oxygen desaturation index by 26.9% ("Odour": 12.5 (15.8), "Control": 25.7 (25.9), z = -3.337, p = 0.000846, BF10 = 9.522). This effect was not linked to the severity of baseline obstructive sleep apnea markers (ρ = -0.042, p = 0.87). Olfactory stimulation did not arouse from sleep or affect sleep structure, measured as time per sleep stage (F1,16 = 0.088, p = 0.77). In conclusion, olfactory stimulation during sleep was effective in reducing the severity of obstructive sleep apnea markers without inducing arousals, and may provide a novel treatment for obstructive sleep apnea, prompting continued research.

FDA-cleared home sleep apnea testing devices

The demand for home sleep apnea testing (HSAT) devices is escalating, particularly in the context of the coronavirus 2019 (COVID-19) pandemic. The absence of standardized development and verification procedures poses a significant challenge. This study meticulously analyzed the approval process characteristics of HSAT devices by the U.S. Food and Drug Administration (FDA) from September 1, 2003, to September 1, 2023, with a primary focus on ensuring safety and clinical effectiveness. We examined 58 reports out of 1046 that underwent FDA clearance via the 510(k) and de novo pathways. A substantial surge in certifications after the 2022 pandemic was observed. Type-3 devices dominated, signifying a growing trend for both home and clinical use. Key measurement items included respiration and sleep analysis, with the apnea–hypopnea index (AHI) and sleep stage emerging as pivotal indicators. The majority of FDA-cleared HSAT devices adhered to electrical safety and biocompatibility standards. Critical considerations encompass performance and function testing, usability, and cybersecurity. This study emphasized the nearly indispensable role of clinical trials in ensuring the clinical effectiveness of HSAT devices. Future studies should propose guidances that specify stringent requirements, robust clinical trial designs, and comprehensive performance criteria to guarantee the minimum safety and clinical effectiveness of HSATs.

“Counting sheep PSG”: EEGLAB-compatible open-source matlab software for signal processing, visualization, event marking and staging of polysomnographic data

BackgroundProgress in advancing sleep research employing polysomnography (PSG) has been negatively impacted by the limited availability of widely available, open-source sleep-specific analysis tools. New methodHere, we introduce Counting Sheep PSG, an EEGLAB-compatible software for signal processing, visualization, event marking and manual sleep stage scoring of PSG data for MATLAB. ResultsKey features include: (1) signal processing tools including bad channel interpolation, down-sampling, re-referencing, filtering, independent component analysis, artifact subspace reconstruction, and power spectral analysis, (2) customizable display of polysomnographic data and hypnogram, (3) event marking mode including manual sleep stage scoring, (4) automatic event detections including movement artifact, sleep spindles, slow waves and eye movements, and (5) export of main descriptive sleep architecture statistics, event statistics and publication-ready hypnogram. Comparison with existing methodsCounting Sheep PSG was built on the foundation created by sleepSMG (https://sleepsmg.sourceforge.net/). The scope and functionalities of the current software have made significant advancements in terms of EEGLAB integration/compatibility, preprocessing, artifact correction, event detection, functionality and ease of use. By comparison, commercial software can be costly and utilize proprietary data formats and algorithms, thereby restricting the ability to distribute and share data and analysis results. ConclusionsThe field of sleep research remains shackled by an industry that resists standardization, prevents interoperability, builds-in planned obsolescence, maintains proprietary black-box data formats and analysis approaches. This presents a major challenge for the field of sleep research. The need for free, open-source software that can read open-format data is essential for scientific advancement to be made in the field.

Insights from the 2nd China intelligent sleep staging competition.

Artificial intelligence (AI) is quickly advancing in the field of sleep medicine, which bodes well for the potential of actual clinical use. In this study, an analysis of the 2nd China Intelligent Sleep Staging Competition was conducted to gain insights into the general level and constraints of AI-assisted sleep staging in China. The outcomes of 10 teams from the children's track and 13 teams from the adult track were investigated in this study. The analysis included overall performance, differences between five different sleep stages, variations across subjects, and performance during stage transitions. The adult track's accuracy peaked at 80.46%, while the children's track's accuracy peaked at 88.96%. On average, accuracy rates stood at 71.43% for children and 68.40% for adults. All results were produced within a mere 5-min timeframe. The N1 stage was prone to misclassification as W, N2, and R stages. In the adult track, significant differences were apparent among subjects (p < 0.05), whereas in the children's track, such differences were not observed. Nonetheless, both tracks experienced a performance decline during stage transitions. The computational speed of AI is remarkably fast, simultaneously holding the potential to surpass the accuracy of physicians. Improving the machine learning model's classification of the N1 stage and transitional periods between stages, along with bolstering its robustness to individual subject variations, is imperative for maximizing its ability in assisting clinical scoring.