Sleep (system call)

About: Sleep (system call) is a research topic. Over the lifetime, 2633 publications have been published within this topic receiving 27806 citations. The topic is also known as: Sleep() & sleep().

Determining whether to change a time at which an alarm is to occur based at least in part on sleep data

Abstract: In one aspect, a device includes a processor and a memory accessible to the processor. The memory bears instructions executable by the processor to receive data from a sleep sensor in communication with the device and, based at least in part on the data, determine whether to change a time at which an alarm is to occur at the device.

A telemedicine program for diagnosis and management of sleep-disordered breathing: the fast-track for sleep apnea tele-sleep program.

Abstract: The objective of this study was to facilitate access to sleep health care for veterans. We designed and implemented a Telehealth program for diagnosing and treating sleep-related breathing disorders (SRBDs). Building on our ongoing out-of-laboratory “Fast Track for Sleep Apnea” program, procedures were modified to accommodate remote operations. This Tele-sleep program was set up at the medical center's community-based outpatient clinics. Home sleep testing and positive airway pressure device technological advances enabled realizing this application for Telehealth. In addition to obtaining appropriated teleconferencing equipment, the program involved implementing systematic processes for (1) six types of clinic visits, (2) training remote-site personnel, (3) making recommendations for inventory management, and (4) evaluating patient satisfaction. Over the past year, we have updated and refined our procedures to optimize program performance and efficiency. To achieve the next step, that is, increasing program scale beyond its current state (e.g., to region-wide), we will need to further develop and formalize quality control indicators to more efficiently monitor operations. The program has helped relieve clinical load at the central sleep program, improved local access to sleep care for veterans, and improved patient satisfaction with health care for SRBDs.

Method and apparatus of sleep mode operation

Abstract: Disclosed herein relates to a sleep mode operation method, and the sleep mode operation method according to the present invention may include transmitting a sleep request message for requesting sleep mode switching to a base station; receiving a sleep operating parameter including a sleep cycle and a listening window from the base station; referring to the sleep operating parameter to switch to a sleep mode; receiving a traffic indication message indicating that traffic is generated from the base station; receiving traffic from the base station during the listening window while at the same time operating a timer; and early terminating the listening window to enter into a sleep window if the timer operation is expired according to the traffic reception prior to terminating the listening window.

Performance of Four Commercial Wearable Sleep-Tracking Devices Tested Under Unrestricted Conditions at Home in Healthy Young Adults

Abstract: Commercial wearable sleep-tracking devices are growing in popularity and in recent studies have performed well against gold standard sleep measurement techniques. However, most studies were conducted in controlled laboratory conditions. We therefore aimed to test the performance of devices under naturalistic unrestricted home sleep conditions.Healthy young adults (n = 21; 12 women, 9 men; 29.0 ± 5.0 years, mean ± SD) slept at home under unrestricted conditions for 1 week using a set of commercial wearable sleep-tracking devices and completed daily sleep diaries. Devices included the Fatigue Science Readiband, Fitbit Inspire HR, Oura ring, and Polar Vantage V Titan. Participants also wore a research-grade actigraphy watch (Philips Respironics Actiwatch 2) for comparison. To assess performance, all devices were compared with a high performing mobile sleep electroencephalography headband device (Dreem 2). Analyses included epoch-by-epoch and sleep summary agreement comparisons.Devices accurately tracked sleep-wake summary metrics (ie, time in bed, total sleep time, sleep efficiency, sleep latency, wake after sleep onset) on most nights but performed best on nights with higher sleep efficiency. Epoch-by-epoch sensitivity (for sleep) and specificity (for wake), respectively, were as follows: Actiwatch (0.95, 0.35), Fatigue Science (0.94, 0.40), Fitbit (0.93, 0.45), Oura (0.94, 0.41), and Polar (0.96, 0.35). Sleep stage-tracking performance was mixed, with high variability.As in previous studies, all devices were better at detecting sleep than wake, and most devices compared favorably to actigraphy in wake detection. Devices performed best on nights with more consolidated sleep patterns. Unrestricted sleep TIB differences were accurately tracked on most nights. High variability in sleep stage-tracking performance suggests that these devices, in their current form, are still best utilized for tracking sleep-wake outcomes and not sleep stages. Most commercial wearables exhibited promising performance for tracking sleep-wake in real-world conditions, further supporting their consideration as an alternative to actigraphy.