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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().


Papers
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Journal ArticleDOI
TL;DR: A validated continuous measure of sleep depth and quality based on automatic analysis of physiologic sleep data, termed Wake Propensity (WP), is used to investigate temporal changes of sleep in response to nocturnal noise events in 3-s epochs to identify event-related shifts towards wakefulness and less deep, more unstable sleep.

10 citations

Journal ArticleDOI
TL;DR: In this paper , the authors examined the relationship between TRE and CVD, with sleep as a potential mediator in this relationship, and proposed a research agenda to investigate this relationship.
Abstract: Cardiovascular disease (CVD) poses a serious health and economic burden worldwide. Modifiable lifestyle factors are a focus of research into reducing the burden of CVD, with diet as one of the most investigated factors. Specifically, the timing and regularity of food intake is an emerging research area, with approaches such as time-restricted eating (TRE) receiving much attention. TRE involves shortening the time available to eat across the day and is associated with improved CVD outcomes compared with longer eating windows. However, studies that have examined TRE have not considered the impact of sleep on CVD outcomes despite recent evidence showing that sleep duration can influence the timing and amount of food eaten. In this article, we argue that as TRE and sleep influence each other, and influence the same cardiometabolic parameters, experiencing inadequate sleep may attenuate any positive impact TRE has on CVD. We examine the relationship between TRE and CVD, with sleep as a potential mediator in this relationship, and propose a research agenda to investigate this relationship. This will provide necessary evidence to inform future interventions aimed at reducing the burden of CVD.

10 citations

Patent
31 Mar 2015
TL;DR: In this paper, a user sleep model is trained using a dataset that includes previously-sensed data, descriptive information associated with the previously sensed data, and/or interpretive data extracted from the previously sensed data describing circumstances surrounding users when the data was acquired.
Abstract: Methods, computer systems, and computer storage media are provided for inferring sleep-related aspects for a user based, in part, on sensor data reflecting user activity detected by one or more sensors. In an embodiment, a user sleep model is trained using a dataset that includes previously-sensed data, descriptive information associated with the previously-sensed data, and/or interpretive data extracted from the previously-sensed data describing circumstances surrounding users when the data was acquired. In an embodiment, services providing time-sensitive recommendations personalized for a user's sleeping pattern using the inferred sleep-related aspects.

10 citations

Patent
25 Feb 2015
TL;DR: In this paper, a method of detecting sleep disturbances is proposed, which comprises: sensing from a body part of a subject a subject signal indicative of a sleep state of the subject; sensing from an environment containing the subject an environment signal indicative in a state of an environment; identifying awakening and/or arousal events based on the subject signal, and changes in the environment state based on environment signal; and correlating the awakening and arousal events to the changes in an environment state, thereby detecting the sleep disturbances.
Abstract: A method of detecting sleep disturbances is disclosed. The method comprises: sensing from a body part of a subject a subject signal indicative of a sleep state of the subject; sensing from an environment containing the subject an environment signal indicative of a state of the environment; identifying awakening and/or arousal events based on the subject signal, and changes in the environment state based on the environment signal; and correlating the awakening and/or arousal events to the changes in the environment state, thereby detecting the sleep disturbances.

10 citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202422
20233,172
20225,977
2021175
2020191
2019236