Background: Obstructive sleep apnea (OSA) has a high prevalence, with an estimated 425 million adults with apnea hypopnea index (AHI) of ≥15 events/hour, and is significantly underdiagnosed. This presents a significant pain point for both the sufferers, and for healthcare systems, particularly in a post COVID-19 pandemic world. As such, it presents an opportunity for new technologies that can enable screening in both developing and developed countries. In this work, the performance of a non-contact OSA screener App that can run on both Apple and Android smartphones is presented. Methods: The subtle breathing patterns of a person in bed can be measured via a smartphone using the "Firefly" app technology platform [and underpinning software development kit (SDK)], which utilizes advanced digital signal processing (DSP) technology and artificial intelligence (AI) algorithms to identify detailed sleep stages, respiration rate, snoring, and OSA patterns. The smartphone is simply placed adjacent to the subject, such as on a bedside table, night stand or shelf, during the sleep session. The system was trained on a set of 128 overnights recorded at a sleep laboratory, where volunteers underwent simultaneous full polysomnography (PSG), and "Firefly" smartphone app analysis. A separate independent test set of 120 recordings was collected across a range of Apple iOS and Android smartphones, and withheld for performance evaluation by a different team. An operating point tuned for mid-sensitivity (i.e., balancing sensitivity and specificity) was chosen for the screener. Results:The performance on the test set is comparable to ambulatory OSA screeners, and other smartphone screening apps, with a sensitivity of 88.3% and specificity of 80.0% [with receiver operating characteristic (ROC) area under the curve (AUC) of 0.92], for a clinical threshold for the AHI of ≥15 events/ hour of detected sleep time. Conclusions: The "Firefly" app based sensing technology offers the potential to significantly lower the barrier of entry to OSA screening, as no hardware (other than the user's personal smartphone) is required.Additionally, multi-night analysis is possible in the home environment, without requiring the wearing of a portable PSG or other home sleep test (HST).

MAP patients show distinct patterns of impaired white matter integrity of global nature relative to controls and the MA group. Future work to investigate the precise nature and timing of alterations in MAP is needed. The results are further suggestive of frontal white matter pathology playing a role in impulsivity in MA dependence and MAP. Hum Brain Mapp 37:2055-2067, 2016. © 2016 Wiley Periodicals, Inc.

Study Objectives This study deals with the question whether a slow (non-disturbing) reduction of core body temperature (CBT) during sleep increases sleep stage N3 and EEG slow wave energy (SWE) and leads to a slowing of heart rate in humans. Participants Thirty-two healthy male subjects with a mean ± SD age 46 ± 4 years and body mass index 25.2 ± 1.8 kg/m2. Methods A high-heat capacity mattress (HM) was used to lower body temperatures in sleep and was compared to a conventional low-heat capacity mattress (LM) in a double-blinded fashion. Polysomnography was performed accompanied by measurements of skin-, core body- and mattress surface-temperatures, and heart rate. EEG power spectral analyses were carried out using Fast Fourier Transform. Interbeat intervals were derived from the electrocardiogram. Results The HM led to a larger decline in CBT, mediated through higher heat conduction from the core via the proximal back skin onto the mattress together with reduced heart rate. These effects occurred together with a significant increase in sleep stage N3 and standardized slow wave energy (sSWE, 0.791–4.297 Hz) accumulated in NREM sleep. In the 2nd half of the night sSWE increase was significantly correlated with body temperature changes, for example with CBT decline in the same phase. Conclusions A HM subtly decreases CBT, leading to an increased amount of sleep stage N3 and of sSWE, as well as a slowing of heart rate.

In this randomized, double-blind, placebo-controlled, two-period crossover study, the effect of the dual orexin receptor antagonist daridorexant was evaluated on nighttime respiratory function and sleep in 28 patients with mild and moderate obstructive sleep apnea (OSA). In each period, 50 mg daridorexant or placebo was administered every evening for 5 days. The primary endpoint was apnea/hypopnea index (AHI) during total sleep time (TST) after the last dosing. Other endpoints included peripheral oxygen saturation (SpO2), sleep duration, latency to persistent sleep (LPS), wake after sleep onset (WASO), and sleep efficiency index (SEI). Pharmacokinetics, safety, and tolerability were also assessed. The mean treatment difference for AHI during TST (i.e. daridorexant − placebo) after the last dosing was 0.74 events/hour (90% confidence interval [CI]: –1.43, 2.92). The corresponding treatment difference for SpO2 during TST was 0.16% [90% CI: –0.21, 0.53]. Overall, there was no clinically relevant effect of daridorexant on AHI or SpO2-related data after single and repeated dosing irrespective of sleep phase (i.e. rapid eye movement [REM] vs non-REM). Moreover, after single and repeated dosing, daridorexant prolonged TST by 39.6 minutes (90% CI: 16.9, 62.3) and 38.8 minutes (19.7, 57.9), respectively, compared with placebo and favorably modulated other sleep-related endpoints (i.e. increased SEI, decreased WASO, and shortened LPS). It attained expected plasma concentrations and was well tolerated in patients with mild and moderate OSA. These results indicate that single and repeated doses of 50 mg daridorexant do not impair nighttime respiratory function and improve sleep in patients with mild and moderate OSA. Clinical Trial Registration ClinicalTrials.gov NCT03765294. A study to investigate the effects of ACT-541468 on nighttime respiratory function in patients with mild to moderate obstructive sleep apnea. https://clinicaltrials.gov/ct2/show/ NCT03765294.

This paper assesses the performance of a new noncontact sensing system based on Sonar technology as a Sleep Disordered Breathing (SDB) screener. The respiration and movements of a subject in bed can be measured via a smartphone placed onto a bedside table equipped with a custom app. The app employs novel proprietary algorithms to identify sleep stages and detect SDB patterns. The SDB screener was trained on a set of 94 overnights recorded at a sleep laboratory, where volunteers underwent simultaneous monitoring via a full polysomnography (PSG) system and a smartphone equipped with the app. An additional fully independent set of 68 recordings, uniformly distributed across SDB severity classes, were held out for independent testing. The performance on the test set is excellent and comparable to other existing ambulatory SDB screeners, with a sensitivity of 94% and specificity of 97%, for a clinical threshold for the Apnea Hypopnea Index (AHI) of 15 events/hour. The technology can easily be adopted to scale, as no purchase of dedicated sensors is needed, providing a much needed lowcost alternative for monitoring and potentially screening of large population segments. Furthermore, the non-invasive, contactless sensing does not interfere with the sleeping habits of the user, facilitating longitudinal assessment. This, in combination with the simultaneous measurement of the user's sleep quality, could provide invaluable insights in the subject's response to SDB therapy and lead to increased patient adherence.