Performance of an ambulatory electroencephalogram sleep monitor in patients with psychiatric disorders

Sleep assessment using EEG-based wearables - A systematic review

Polysomnography (PSG) is the reference standard of sleep measurement, but is burdensome for the participant and labor intensive. Affordable electroencephalography (EEG)-based wearables are easy to use and are gaining popularity, yet selecting the most suitable device is a challenge for clinicians and researchers. In this systematic review, we aim to provide a comprehensive overview of available EEG-based wearables to measure human sleep. For each wearable, an overview will be provided regarding validated population and reported measurement properties. A systematic search was conducted in the databases OVID MEDLINE, Embase.com and CINAHL. A machine learning algorithm (ASReview) was utilized to screen titles and abstracts for eligibility. In total, 60 papers were selected, covering 34 unique EEG-based wearables. Feasibility studies indicated good tolerance, high compliance, and success rates. The 42 included validation studies were conducted across diverse populations and showed consistently high accuracy in sleep staging detection. Therefore, the recent advancements in EEG-based wearables show great promise as alternative for PSG and for at-home sleep monitoring. Users should consider factors like user-friendliness, comfort, and costs, as these devices vary in features and pricing, impacting their suitability for individual needs.

Assessing the Real-World, Long-Term Impact of Lemborexant on Sleep Quality in a Home-Based Clinical Study

Purpose

Both subjective and objective evaluations are essential for the treatment of insomnia. Lemborexant has been shown to be effective in the long-term based solely on a subjective basis, and no long-term objective measures have been evaluated under natural sleep conditions. Small, lightweight sleep electroencephalogram (EEG) monitor was used, instead of polysomnography, to objectively evaluate sleep at home 4 and 12 weeks after lemborexant treatment.

Patients and Methods

Adults and elderly subjects with insomnia disorder, per the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, were enrolled in this open-label, single-arm, single-center trial. Objective and subjective measures of sleep were prospectively assessed. Sleep disturbance, excessive sleepiness, and depressive symptoms were assessed using questionnaires.

Results

A total of 45 subjects were screened, of which 33 were enrolled. Paired t-tests were conducted to evaluate changes in sleep variables and compared with the baseline; subjects showed significant improvements in objective sleep efficiency (SE) and subjective sleep parameters at weeks 4 and 12 following treatment with lemborexant. When baseline values were taken into account, a repeated-multivariate analysis of variance (MANOVA) revealed statistically significant changes in the objective measures. Sleep disturbance, excessive sleepiness, and depressive symptoms improved after three months of lemborexant treatment.

Conclusion

Furthermore, lemborexant therapy improved nocturnal sleep, when measured objectively using sleep EEG monitoring at home, and improved daytime sleepiness and depressive symptoms in older adults with insomnia disorder.

Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study

BACKGROUND

Sleep disturbances are core symptoms of psychiatric disorders. Although various sleep measures have been developed to assess sleep patterns and quality of sleep, the concordance of these measures in patients with psychiatric disorders remains relatively elusive.

OBJECTIVE

This study aims to examine the degree of agreement among 3 sleep recording methods and the consistency between subjective and objective sleep measures, with a specific focus on recently developed devices in a population of individuals with psychiatric disorders.

METHODS

We analyzed 62 participants for this cross-sectional study, all having data for polysomnography (PSG), Zmachine, Fitbit, and sleep logs. Participants completed questionnaires on their symptoms and estimated sleep duration the morning after the overnight sleep assessment. The interclass correlation coefficients (ICCs) were calculated to evaluate the consistency between sleep parameters obtained from each instrument. Additionally, Bland-Altman plots were used to visually show differences and limits of agreement for sleep parameters measured by PSG, Zmachine, Fitbit, and sleep logs.

RESULTS

The findings indicated a moderate agreement between PSG and Zmachine data for total sleep time (ICC=0.46; P<.001), wake after sleep onset (ICC=0.39; P=.002), and sleep efficiency (ICC=0.40; P=.006). In contrast, Fitbit demonstrated notable disagreement with PSG (total sleep time: ICC=0.08; wake after sleep onset: ICC=0.18; sleep efficiency: ICC=0.10) and exhibited particularly large discrepancies from the sleep logs (total sleep time: ICC=-0.01; wake after sleep onset: ICC=0.05; sleep efficiency: ICC=-0.02). Furthermore, subjective and objective concordance among PSG, Zmachine, and sleep logs appeared to be influenced by the severity of the depressive symptoms and obstructive sleep apnea, while these associations were not observed between the Fitbit and other sleep instruments.

CONCLUSIONS

Our study results suggest that Fitbit accuracy is reduced in the presence of comorbid clinical symptoms. Although user-friendly, Fitbit has limitations that should be considered when assessing sleep in patients with psychiatric disorders.

Exploratory Validation of Sleep-Tracking Devices in Patients with Psychiatric Disorders

Purpose

Sleep-tracking devices have performed well in recent studies that evaluated their use in healthy adults by comparing them with the gold standard sleep assessment technique, polysomnography (PSG). These devices have not been validated for use in patients with psychiatric disorders. Therefore, we tested the performance of three sleep-tracking devices against PSG in patients with psychiatric disorders.

Patients and methods

In total, 52 patients (32 women; 48.1 ± 17.2 years, mean ± SD; 18 patients diagnosed with schizophrenia, 19 with depressive disorder, 3 with bipolar disorder, and 12 with sleep disorder cases) were tested in a sleep laboratory with PSG, along with portable electroencephalography (EEG) device (Sleepgraph), actigraphy (MTN-220/221) and consumer sleep-tracking device (Fitbit Sense).

Results

Epoch-by-epoch sensitivity (for sleep) and specificity (for wake), respectively, were as follows: Sleepgraph (0.95, 0.76), Fitbit Sense (0.95, 0.45) and MTN-220/221 (0.93, 0.40). Portable EEG (Sleepgraph) had the best sleep stage-tracking performance. Sleep-wake summary metrics demonstrated lower performance on poor sleep (ice, shorter total sleep time, lower sleep efficiency, longer sleep latency, longer wake after sleep onset).

Conclusion

Devices demonstrated similar sleep-wake detecting performance as compared with previous studies that evaluated sleep in healthy adults. Consumer sleep device may exhibit poor sleep stage-tracking performance in patients with psychiatric disorders due to factors that affect the sleep determination algorithm, such as changes in autonomic nervous system activity. However, Sleepgraph, a portable EEG device, demonstrated higher performance in mental disorders than the Fitbit Sense and actigraphy.

A Study of Factors Causing Sleep State Misperception in Patients with Depression

PURPOSE

Sleep state misperception, which is the discrepancy between subjective and objective sleep, is often observed in patients with depression. This phenomenon may delay the remission of depression. Previous studies have focused on the total sleep time (TST) misperception, with many of these studies using actigraphy. Thus, our study investigated depressed patients with the exploratory aim of clarifying factors associated with the sleep state misperception including the wake after sleep onset (WASO) misperception, with their objective sleep additionally evaluated by polysomnography (PSG).

PATIENTS AND METHODS

We conducted a cross-sectional study. Before undergoing overnight PSG monitoring, 40 patients with depression completed questionnaires that included the Beck Depression Inventory (BDI), Epworth sleepiness scale, Temperament and Character Inventory, and the Pittsburgh sleep quality index. Patients were also asked to estimate their subjective sleep duration after they woke up in the morning. Based on this data, we calculated the misperception using the following formula: subjective sleep duration minus objective sleep duration. We compared each factor between negative and positive misperception groups and the multiple regression analysis was performed for TST and WASO misperception, respectively.

RESULTS

Although sleep architectures, age, severity of depression and obstructive sleep apnea (OSA) exhibited differences in underestimating or overestimating the WASO, only sex differences were associated with underestimating or overestimating their total sleep time (TST). Moreover, BDI, the severity of OSA, sleep architectures (N1% and N2%), and benzodiazepine (BZD) use were significantly correlated with WASO misperception, whereas only OSA severity was significantly correlated with TST misperception. A subsequent multiple regression analysis demonstrated the BDI was independently correlated with the WASO misperception (β=0.341, p=0.049).

CONCLUSION

In clinical practice, interventions especially for OSA, and the reduction of depressive symptoms are an important method for improving patient sleep perception. Moreover, current results suggest that BZD prescriptions should be avoided as well.

FLUID study: study protocol for an open-label, single-centre pilot study to investigate the efFect of Lemborexant on sleep management in Japanese sUbjects aged 50 years and older with Insomnia Disorder

INTRODUCTION

Bidirectional associations have been reported between sleep disturbance and both cognitive impairment, including Alzheimer's disease and amyloid beta-peptide (Aβ) accumulation. These relationships can be explained by the glymphatic system, which acts as a garbage drainage system in the brain. As interstitial fluid dynamics are suggested to increase during sleep, clearance of Aβ can be influenced by sleep disturbance or deprivation. We hypothesised that using lemborexant, an orexin receptor antagonist, to improve sleep quality would also improve the function of the glymphatic system. We plan to examine the effect of lemborexant on sleep quality and the glymphatic system among patients with insomnia disorder.

METHODS AND ANALYSIS

This pilot study is designed as an open-label, single-arm, single-centre trial. Thirty patients aged 50 years and over with insomnia will be recruited. The participants will take lemborexant (5 mg) at bedtime for 12 weeks and undergo a home-based sleep study at baseline and weeks 4 and 12, as well as MRI examinations to evaluate the glymphatic system at baseline and week 12. The primary outcome will be changes in objective sleep parameters as evaluated using a sleep monitoring system. The secondary outcomes will be changes in subjective sleep parameters. The relationships between changes in sleep parameters and the glymphatic system will be evaluated using diffusion tensor image analysis along the perivascular space, which is called the ALPS-index. Sleep parameters and the ALPS-index will be analysed using a paired t-test or Pearson's correlation coefficient.

ETHICS AND DISSEMINATION

The study protocol was approved by Nagoya University Certified Review Board. The findings from this research will be published in peer-reviewed journals and be presented at local, national and international conferences.

TRIAL REGISTRATION NUMBER

jRCTs041210024.