The accurate assessment of sleep is critical to better understand and evaluate its role in health and disease. The boom in wearable technology is part of the digital health revolution and is producing many novel, highly sophisticated and relatively inexpensive consumer devices collecting data from multiple sensors and claiming to extract information about users' behaviors, including sleep. These devices are now able to capture different biosignals for determining, for example, HR and its variability, skin conductance, and temperature, in addition to activity. They perform 24/7, generating overwhelmingly large data sets (big data), with the potential of offering an unprecedented window on users' health. Unfortunately, little guidance exists within and outside the scientific sleep community for their use, leading to confusion and controversy about their validity and application. The current state-of-the-art review aims to highlight use, validation and utility of consumer wearable sleep-trackers in clinical practice and research. Guidelines for a standardized assessment of device performance is deemed necessary, and several critical factors (proprietary algorithms, device malfunction, firmware updates) need to be considered before using these devices in clinical and sleep research protocols. Ultimately, wearable sleep technology holds promise for advancing understanding of sleep health; however, a careful path forward needs to be navigated, understanding the benefits and pitfalls of this technology as applied in sleep research and clinical sleep medicine.

/pdf/wearable-sleep-technology-in-clinical-and-research-settings-9ijyvopq3s.pdf

Wearable Sleep Technology in Clinical and Research Settings.

Skin-mounted soft electronics that incorporate high-bandwidth triaxial accelerometers can capture broad classes of physiologically relevant information, including mechano-acoustic signatures of underlying body processes (such as those measured by a stethoscope) and precision kinematics of core-body motions. Here, we describe a wireless device designed to be conformally placed on the suprasternal notch for the continuous measurement of mechano-acoustic signals, from subtle vibrations of the skin at accelerations of around 10−3 m s−2 to large motions of the entire body at about 10 m s−2, and at frequencies up to around 800 Hz. Because the measurements are a complex superposition of signals that arise from locomotion, body orientation, swallowing, respiration, cardiac activity, vocal-fold vibrations and other sources, we exploited frequency-domain analysis and machine learning to obtain—from human subjects during natural daily activities and exercise—real-time recordings of heart rate, respiration rate, energy intensity and other essential vital signs, as well as talking time and cadence, swallow counts and patterns, and other unconventional biomarkers. We also used the device in sleep laboratories and validated the measurements using polysomnography. A wireless device designed to be conformally placed on the suprasternal notch can continuously provide real-time information of essential vital signs as well as talking time, swallow counts and sleep patterns.

/pdf/mechano-acoustic-sensing-of-physiological-processes-and-body-15tn4nfcir.pdf

Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch

Dynamic coupling between the central and autonomic nervous systems during sleep: A review.

One-seventh of the world's adult population, or approximately one billion people, are estimated to have OSA. Over the past four decades, obesity, the main risk factor for OSA, has risen in striking proportion worldwide. In the past 5 years, the WHO estimates global obesity to affect almost two billion adults. A second major risk factor for OSA is advanced age. As the prevalence of the ageing population and obesity increases, the vulnerability towards having OSA increases. In addition to these traditional OSA risk factors, studies of the global population reveal select contributing features and phenotypes, including extreme phenotypes and symptom clusters that deserve further examination. Untreated OSA is associated with significant comorbidities and mortality. These represent a tremendous threat to the individual and global health. Beyond the personal toll, the economic costs of OSA are far-reaching, affecting the individual, family and society directly and indirectly, in terms of productivity and public safety. A better understanding of the pathophysiology, individual and ethnic similarities and differences is needed to better facilitate management of this chronic disease. In some countries, measures of the OSA disease burden are sparse. As the global burden of OSA and its associated comorbidities are projected to further increase, the infrastructure to diagnose and manage OSA will need to adapt. The use of novel approaches (electronic health records and artificial intelligence) to stratify risk, diagnose and affect treatment are necessary. Together, a unified multi-disciplinary, multi-organizational, global approach will be needed to manage this disease.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/resp.13838

Global burden of sleep‐disordered breathing and its implications

Benefits in long-term memory retention and generalization have been shown to be related to sleep-dependent processes, which correlate with neural oscillations as measured by changes in electric potential. The specificity and causal role of these oscillations, however, are still poorly understood. Here, we investigated the potential for augmenting endogenous slow-wave (SW) oscillations in humans with closed-loop transcranial alternating current stimulation (tACS) with an aim toward enhancing the consolidation of recent experiences into long-term memory. Sixteen (three female) participants were trained presleep on a target detection task identifying targets hidden in complex visual scenes. During post-training sleep, closed-loop SW detection and stimulation were used to deliver tACS matching the phase and frequency of the dominant oscillation in the range of 0.5-1.2 Hz. Changes in performance were assessed the following day using test images that were identical to the training ("repeated"), and images generated from training scenes but with novel viewpoints ("generalized"). Results showed that active SW tACS during sleep enhanced the postsleep versus presleep target detection accuracy for the generalized images compared with sham nights, while no significant change was found for repeated images. Using a frequency-agnostic clustering approach sensitive to stimulation-induced spectral power changes in scalp EEG, this behavioral enhancement significantly correlated with both a poststimulation increase and a subsequent decrease in measured spectral power within the SW band, which in turn showed increased coupling with spindle amplitude. These results suggest that augmenting endogenous SW oscillations can enhance consolidation by specifically improving generalization over recognition or cued recall.SIGNIFICANCE STATEMENT This human study demonstrates the use of a closed-loop noninvasive brain stimulation method to enhance endogenous neural oscillations during sleep with the effect of improving consolidation of recent experiences into long-term memory. Here we show that transient slow oscillatory transcranial alternating current stimulation (tACS) triggered by endogenous slow oscillations and matching their frequency and phase can increase slow-wave power and coupling with spindles. Further, this increase correlates with overnight improvements in generalization of recent training to facilitate performance in a target detection task. We also provide novel evidence for a tACS-induced refractory period following the tACS-induced increase. Here slow-wave power is temporarily reduced relative to sham stimulation, which nonetheless maintains a positive relationship with behavioral improvements.

https://www.jneurosci.org/content/jneuro/38/33/7314.full.pdf

Closed-Loop Slow-Wave tACS Improves Sleep-Dependent Long-Term Memory Generalization by Modulating Endogenous Oscillations.

AASM Scoring Manual Updates for 2017 (Version 2.4).

V 2.2 of the American Academy of Sleep Medicine (AASM) Manual for the Scoring of Sleep and Associated Events was released on July 1, 2015. The Scoring Manual Editorial Board (previously the Scoring Manual Committee) would like to call attention to the most important changes. As discussed below, there are two new major chapters providing rules for the staging of infant sleep and scoring respiratory events in home sleep apnea testing (HSAT) studies. The new chapters were approved by the AASM Board of Directors to fi ll two obvious gaps in the Scoring Manual. The Scoring Manual Editorial Board would like to emphasize that any changes in the manual are instituted after long deliberation and consultation with area content experts. Version 2.2 of the Scoring Manual, for the fi rst time, includes rules for scoring sleep studies in term infants less than two months of age. This milestone acknowledges the importance of studying sleep across the lifespan, beginning with our youngest patients. The new scoring rules address sleep staging in infants and are based on the classic infant scoring rules of Anders et al.1 Development of these new rules benefi tted from expert consultation from Madeleine Grigg-Damberger, MD, and Mark Scher, MD. One important difference between the current manual and Anders is that sleep is now classifi ed into three stages: REM, NREM and transitional, as compared to the Anders classifi cation of active, quiet and indeterminate sleep. This new classifi cation was based on the physiologic similarities between active and REM sleep, and quiet and NREM sleep. Further, it was realized that young infants have stages of sleep that manifest elements of both REM and NREM sleep; hence, the term “transitional” rather than “indeterminate.” Note that respiratory events in infants should be scored using the standard AASM pediatric scoring criteria. Version 2.2 of the AASM Scoring Manual now also includes scoring rules for adult Home Sleep Apnea Testing (HSAT; chapter IX). The foundation for the development of these rules includes the work of the 2010 AASM Out-of-Center Task Force who developed the SCOPER (Sleep, Cardiovascular, Oximetry, Position, Effort, Respiratory) classifi cation system.2 This classifi cation system systematically evaluated available technology and evidence for diagnosing obstructive sleep apnea using portable devices. These new HSAT scoring rules allow for standardization of scoring and reporting data generated from HSAT AASM Scoring Manual Version 2.2 Updates: New Chapters for Scoring Infant Sleep Staging and Home Sleep Apnea Testing Richard B. Berry, MD1; Charlene E. Gamaldo, MD2; Susan M. Harding, MD3; Rita Brooks, MEd, RST, RPSGT4; Robin M. Lloyd, MD5; Bradley V. Vaughn, MD6; Carole L. Marcus, MBBCh7 1University of Florida, Gainesville, FL; 2Johns Hopkins University, Baltimore, MD; 3University of Alabama, Birmingham, AL; 4Capital Health, Hamilton, NJ; 5Mayo Clinic, Rochester, MN; 6University of North Carolina, Chapel Hill, NC; 7Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA

Rita Brooks

Papers

AASM Scoring Manual Updates for 2017 (Version 2.4).

AASM Scoring Manual Version 2.2 Updates: New Chapters for Scoring Infant Sleep Staging and Home Sleep Apnea Testing.

Should the arousal scoring rule be changed