Self-Applied Home Sleep Recordings: The Future of Sleep Medicine

Feasibility and usability of three consecutive nights with self-applied, home polysomnography

In-laboratory polysomnography, the gold-standard for diagnosing sleep disorders, is resource-demanding and not conducive to multiple night evaluations. Ambulatory polysomnography, especially when self-applied, could be a viable alternative. This study aimed to assess the feasibility and reliability of self-applied polysomnography over three consecutive nights in untrained participants, assessing: technical success rate; comparing sleep diagnostic variables from single and multiple nights; and evaluating participants' subjective experience. Data were collected from 78 participants (55.1% females) invited to test a self-applicable polysomnography device for three consecutive nights at home. The technical success rate for valid sleep recordings was 82.5% out of 234 planned study nights, with 87.2% of participants obtaining at least two valid nights. Misclassification of obstructive sleep apnea severity was higher in participants with mild OSA (21.4%) compared with those with moderate-to-severe obstructive sleep apnea or no obstructive sleep apnea. Sleep efficiency and wake after sleep onset showed improvement from Night 1 to Night 3 (p < 0.001), and the mean polysomnography set-up time decreased significantly over this period. Participants reported moderate-to-high satisfaction with the device (System Usability Scale score 71.2 ± 12.4). The findings suggest that self-applied polysomnography is a feasible diagnostic method for untrained individuals at risk for sleep disorders, and that multiple night assessments can improve diagnostic precision for mild obstructive sleep apnea cases.

Self-applied somnography: technical feasibility of electroencephalography and electro-oculography signal characteristics in sleep staging of suspected sleep-disordered adults

Sleep recordings are increasingly being conducted in patients' homes where patients apply the sensors themselves according to instructions. However, certain sensor types such as cup electrodes used in conventional polysomnography are unfeasible for self-application. To overcome this, self-applied forehead montages with electroencephalography and electro-oculography sensors have been developed. We evaluated the technical feasibility of a self-applied electrode set from Nox Medical (Reykjavik, Iceland) through home sleep recordings of healthy and suspected sleep-disordered adults (n = 174) in the context of sleep staging. Subjects slept with a double setup of conventional type II polysomnography sensors and self-applied forehead sensors. We found that the self-applied electroencephalography and electro-oculography electrodes had acceptable impedance levels but were more prone to losing proper skin-electrode contact than the conventional cup electrodes. Moreover, the forehead electroencephalography signals recorded using the self-applied electrodes expressed lower amplitudes (difference 25.3%-43.9%, p < 0.001) and less absolute power (at 1-40 Hz, p < 0.001) than the polysomnography electroencephalography signals in all sleep stages. However, the signals recorded with the self-applied electroencephalography electrodes expressed more relative power (p < 0.001) at very low frequencies (0.3-1.0 Hz) in all sleep stages. The electro-oculography signals recorded with the self-applied electrodes expressed comparable characteristics with standard electro-oculography. In conclusion, the results support the technical feasibility of the self-applied electroencephalography and electro-oculography for sleep staging in home sleep recordings, after adjustment for amplitude differences, especially for scoring Stage N3 sleep.

Review and perspective on sleep-disordered breathing research and translation to clinics

Sleep-disordered breathing, ranging from habitual snoring to severe obstructive sleep apnea, is a prevalent public health issue. Despite rising interest in sleep and awareness of sleep disorders, sleep research and diagnostic practices still rely on outdated metrics and laborious methods reducing the diagnostic capacity and preventing timely diagnosis and treatment. Consequently, a significant portion of individuals affected by sleep-disordered breathing remain undiagnosed or are misdiagnosed. Taking advantage of state-of-the-art scientific, technological, and computational advances could be an effective way to optimize the diagnostic and treatment pathways. We discuss state-of-the-art multidisciplinary research, review the shortcomings in the current practices of SDB diagnosis and management in adult populations, and provide possible future directions. We critically review the opportunities for modern data analysis methods and machine learning to combine multimodal information, provide a perspective on the pitfalls of big data analysis, and discuss approaches for developing analysis strategies that overcome current limitations. We argue that large-scale and multidisciplinary collaborative efforts based on clinical, scientific, and technical knowledge and rigorous clinical validation and implementation of the outcomes in practice are needed to move the research of sleep-disordered breathing forward, thus increasing the quality of diagnostics and treatment.

Consumer Wearable Sleep Trackers: Are They Ready for Clinical Use?

As the importance of good sleep continues to gain public recognition, the market for sleep-monitoring devices continues to grow. Modern technology has shifted from simple sleep tracking to a more granular sleep health assessment. We examine the available functionalities of consumer wearable sleep trackers (CWSTs) and how they perform in healthy individuals and disease states. Additionally, the continuum of sleep technology from consumer-grade to medical-grade is detailed. As this trend invariably grows, we urge professional societies to develop guidelines encompassing the practical clinical use of CWSTs and how best to incorporate them into patient care plans.

Consumer sleep technology for the screening of obstructive sleep apnea and snoring: current status and a protocol for a systematic review and meta-analysis of diagnostic test accuracy

There are concerns about the validation and accuracy of currently available consumer sleep technology for sleep-disordered breathing. The present report provides a background review of existing consumer sleep technologies and discloses the methods and procedures for a systematic review and meta-analysis of diagnostic test accuracy of these devices and apps for the detection of obstructive sleep apnea and snoring in comparison with polysomnography. The search will be performed in four databases (PubMed, Scopus, Web of Science, and the Cochrane Library). Studies will be selected in two steps, first by an analysis of abstracts followed by full-text analysis, and two independent reviewers will perform both phases. Primary outcomes include apnea-hypopnea index, respiratory disturbance index, respiratory event index, oxygen desaturation index, and snoring duration for both index and reference tests, as well as the number of true positives, false positives, true negatives, and false negatives for each threshold, as well as for epoch-by-epoch and event-by-event results, which will be considered for the calculation of surrogate measures (including sensitivity, specificity, and accuracy). Diagnostic test accuracy meta-analyses will be performed using the Chu and Cole bivariate binomial model. Mean difference meta-analysis will be performed for continuous outcomes using the DerSimonian and Laird random-effects model. Analyses will be performed independently for each outcome. Subgroup and sensitivity analyses will evaluate the effects of the types (wearables, nearables, bed sensors, smartphone applications), technologies (e.g., oximeter, microphone, arterial tonometry, accelerometer), the role of manufacturers, and the representativeness of the samples.

A wearable device for at-home obstructive sleep apnea assessment: State-of-the-art and research challenges

In the last 3 years, almost all medical resources have been reserved for the screening and treatment of patients with coronavirus disease (COVID-19). Due to a shortage of medical staff and equipment, diagnosing sleep disorders, such as obstructive sleep apnea (OSA), has become more difficult than ever. In addition to being diagnosed using polysomnography at a hospital, people seem to pay more attention to alternative at-home OSA detection solutions. This study aims to review state-of-the-art assessment techniques for out-of-center detection of the main characteristics of OSA, such as sleep, cardiovascular function, oxygen balance and consumption, sleep position, breathing effort, respiratory function, and audio, as well as recent progress in the implementation of data acquisition and processing and machine learning techniques that support early detection of severe OSA levels.

Desaturation event scoring criteria affect the perceived severity of nocturnal hypoxic load

OBJECTIVES/BACKGROUND

Interest in using blood oxygen desaturations in the diagnostics of sleep apnea has risen in recent years. However, no standardized criteria for desaturation scoring exist which complicates the drawing of solid conclusions from literature.

PATIENTS/METHODS

We investigated how different desaturation scoring criteria affect the severity of nocturnal hypoxic load and the prediction of impaired daytime vigilance in 845 patients. Desaturations were scored based on three features: 1) minimum oxygen saturation drop during the event (2-20%, 1% interval), 2) minimum duration of the event (2-20s, 1s interval), and 3) maximum plateau duration within the event (5-60s, 5s interval), resulting in 4332 different scoring criteria. The hypoxic load was described with oxygen desaturation index (ODI), desaturation severity (DesSev), and desaturation duration (DesDur) parameters. Association between hypoxic load and impaired vigilance was investigated with covariate-adjusted area under curve (AUC) analyses by dividing patients into normal (≤5 lapses) and impaired (≥36 lapses) vigilance groups based on psychomotor vigilance task performance.

RESULTS

The severity of hypoxic load varied greatly between different scoring criteria. For example, median ODI ranged between 0.4 and 12.9 events/h, DesSev 0.01-0.23 %-point, and DesDur 0.3-9.6 %-point when the minimum transient drop criterion of 3% was used and other two features were altered. Overall, the minimum transient drop criterion had the largest effect on parameter values. All models with differently determined parameters predicted impaired vigilance moderately (AUC = 0.722-0.734).

CONCLUSIONS

Desaturation scoring criteria greatly affected the severity of hypoxic load. However, the difference in the prediction of impaired vigilance between different criteria was rather small.

Effectiveness of Digital Cognitive Behavioral Therapy for Insomnia in Young People: Preliminary Findings from Systematic Review and Meta-Analysis

Various forms of cognitive behavioral therapy for insomnia (CBT-i) have been developed to improve its scalability and accessibility for insomnia management in young people, but the efficacy of digitally-delivered cognitive behavioral therapy for insomnia (dCBT-i) remains uncertain. This study systematically reviewed and evaluated the effectiveness of dCBT-i among young individuals with insomnia. We conducted comprehensive searches using four electronic databases (PubMed, Cochrane Library, PsycINFO, and Embase; until October 2021) and examined eligible records. The search strategy comprised the following three main concepts: (1) participants were adolescents or active college students; (2) dCBT-I was employed; (3) standardized tools were used for outcome measurement. Four randomized controlled trials qualified for meta-analysis. A significant improvement in self-reported sleep quality with a medium-to-large effect size after treatment (Hedges’s g = −0.58~−0.80) was noted. However, a limited effect was detected regarding objective sleep quality improvement (total sleep time and sleep efficiency measured using actigraphy). These preliminary findings from the meta-analysis suggest that dCBT-i is a moderately effective treatment in managing insomnia in younger age groups, and CBT-i delivered through the web or a mobile application is an acceptable approach for promoting sleep health in young people.