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().

Sleep cycle-dependent vascular dynamics in male mice and the predicted effects on perivascular cerebrospinal fluid flow and solute transport

Abstract: Abstract Perivascular spaces are important highways for fluid and solute transport in the brain enabling efficient waste clearance during sleep. However, the underlying mechanisms augmenting perivascular flow in sleep are unknown. Using two-photon imaging of naturally sleeping male mice we demonstrate sleep cycle-dependent vascular dynamics of pial arteries and penetrating arterioles: slow, large-amplitude oscillations in NREM sleep, a vasodilation in REM sleep, and a vasoconstriction upon awakening at the end of a sleep cycle and microarousals in NREM and intermediate sleep. These vascular dynamics are mirrored by changes in the size of the perivascular spaces of the penetrating arterioles: slow fluctuations in NREM sleep, reduction in REM sleep and an enlargement upon awakening after REM sleep and during microarousals in NREM and intermediate sleep. By biomechanical modeling we demonstrate that these sleep cycle-dependent perivascular dynamics likely enhance fluid flow and solute transport in perivascular spaces to levels comparable to cardiac pulsation-driven oscillations.

Epidemiology of accelerometer-based sleep parameters in US school-aged children and adults: NHANES 2011–2014

Abstract: Abstract We aimed to provide objectively measured sleep parameters across lifespan by sex and race in a national representative sample of US population. The study included 11,279 participants 6 years and older from the National Health and Nutrition Examination Survey (NHANES) 2011–2014, who had at least 3 days of valid sleep parameters calculated from 7-day 24-h accelerometer recording. Sleep duration showed a U-shaped association with age and reached the minimum at age 40 and started to increase again around age 50. The clock time for sleep onset (CTSO) delayed with age and reached the maximum at about age 20. CTSO then advanced until age 50, leveled off until age 70, then advanced again after age 70. Sleep efficiency showed an overall decreasing trend across the lifespan but stabilized from age 30 to about age 60. US young adults in age 20 s are the ones who slept at the latest around midnight, while the middle aged US residents between 40 and 50 years old slept the least. Females generally present longer sleep duration than males, while more likely to have later sleep onset, particularly at older ages. Non-Hispanic Blacks showed worse sleep characteristics, i.e. sleep later, sleep shorter, and sleep less efficiently, compared to other racial groups. In conclusion, this study provides valuable insights on the characteristics of sleep habits of residents of the United States by using objectively measurements of sleep parameters and will help guide personalized advice on sleep hygiene.

Automatic sleep detection method and system based on wearable intelligent equipment

Abstract: The invention discloses an automatic sleep detection method and system based on wearable intelligent equipment, and belongs to the field of wearable intelligent equipment The method comprises the steps that original data of an equipment wearer are collected and stored by the wearable intelligent equipment; the original data comprise the interrupt service times recorded by a microcontrol unit of the equipment; sleep data of the equipment wearer are determined according to the original data; the sleep data comprise the sleep starting time, the sleep finishing time and the sleep duration time; the different sleep states of the equipment wearer are partitioned according to the sleep data According to the method and system, automatic detection on the sleep states of the wearable intelligent equipment wearer can be achieved, manual operation of a user is not needed, better humanization is achieved, the user experience is improved, and the requirements of the user of the wearable intelligent equipment are better met

Sleep improvement device and program

Abstract: PROBLEM TO BE SOLVED: To provide a sleep improvement device capable of improving sleep based on an improvement that a user can easily perform. SOLUTION: This sleep improvement device includes a sleep information acquisition section 11 that acquires sleep information from a plurality of sensors, an information processing block 30 that selects information suited to improve the situation of sleep, out of advise information of database 12 based on the sleep information and sets one having a lowest difficulty level for the user out of the selections, as an output target, and a display control section 23 that outputs the advice information, or the output target, to a monitor 4. COPYRIGHT: (C)2010,JPO&INPIT

Sleep depth determining apparatus and method

Abstract: There is provided an apparatus for determining depth of sleep. The apparatus includes a heart rate sensor configured to detect a heart rate of a subject in a non-contact manner, and a processor. The processor performs determining depth of sleep of the subject from the heart rate detected by the heart rate sensor, estimating a sleep cycle of the subject on the basis of a plurality of times at each of which a change in the depth of sleep occurs, and stopping the heart rate sensor, after completion of acquiring the plurality of times, at least until an anticipated time of a change in the depth of sleep.