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 Irregularity and Nonsuicidal Self-injurious Urges and Behaviors.

Abstract: STUDY OBJECTIVES The objectives of this study were to examine the relationships between sleep regularity and nonsuicidal self-injury (NSSI), including lifetime NSSI history and daily NSSI urges. METHODS Undergraduate students (N=119; 18-26 years), approximately half of whom endorsed a lifetime history of repetitive NSSI, completed a 10-day actigraphy and ecological momentary assessment (EMA) protocol. A Sleep Regularity Index was calculated for all participants using scored epoch by epoch data to capture rapid changes in sleep schedules. Participants responded to EMA prompts assessing NSSI urge severity and negative affect three times daily over the 10-day assessment period. RESULTS Results indicate that individuals with a repetitive NSSI history were more likely to experience sleep irregularity than those without a history of NSSI. Findings also suggest that sleep irregularity was associated with more intense urges to engage in NSSI on a daily basis, even after accounting for average daily sleep duration, sleep timing, negative affect, and NSSI history. Neither sleep duration nor sleep timing were associated with NSSI history nor daily NSSI urge intensity. CONCLUSIONS Findings suggest that sleep irregularity is linked with NSSI, including NSSI history and intensity of urges to engage in NSSI. The present study not only supports the growing evidence linking sleep disturbance with risk for self-injury, but also demonstrates this relationship using actigraphy and real-time assessments of NSSI urge severity. Findings highlight the importance of delineating the nuances in sleep irregularity that are proximally associated with NSSI risk and identifying targets for intervention.

Sleep analyzer, program and recording medium

Abstract: PROBLEM TO BE SOLVED: To provide a sleep analyzer, a program and a recording medium, capable of executing easy measurement even in a general home or the like without using a large-scale device such as a sleep polygraphy, and deciding quality of a sleep with an simple index. SOLUTION: At step 100, a pulse wave is measured. At step 110, an pulse interval is found from a (digital-converted) signal from a pulse wave sensor 1. For example, a time that is the interval between a peak of the pulse wave and a peak of the pulse wave is found. At step 120, frequency of the pulse interval is analyzed, and components in a frequency band of 0.15-0.45 Hz are extracted. At step 130, power of the frequency components is integrated to find a sleep quality value (an integration value: an accumulation value). At step 140, the quality of the sleep is decided on the basis of the sleep quality value. COPYRIGHT: (C)2002,JPO

The Lifestyle-Related Cardiovascular Risk Is Modified by Sleep Patterns.

Abstract: To prospectively assess whether sleep patterns modified lifestyle-associated cardiovascular disease (CVD) risk.This study included 393,690 participants without CVD at baseline measurements between March 13, 2006, and October 1, 2010, from UK Biobank. A lifestyle score was calculated on the basis of the 4 lifestyle factors (smoking, alcohol consumption, physical activity, and diet), and sleep patterns were constructed based on sleep duration, chronotype, insomnia, snoring, and daytime dozing.During a median follow-up of 8.93 years, we observed 10,218 incident CVD events, including 6595 myocardial infarctions (MIs) and 3906 strokes. We found that sleep patterns significantly modified the relations of the lifestyle score with incident CVD (P for interaction =.007) and MI (P for interaction =.004). Among participants with a poor sleep pattern, unfavorable lifestyle (per score increase) was associated with 25% (95% CI, 13% to 39%) and 29% (95% CI, 13% to 47%) increased risks for CVD and MI, while among participants with a healthy sleep pattern, unfavorable lifestyle was associated with 18% (95% CI, 15% to 21%) and 17% (95% CI, 13% to 21%) increased risks for CVD and MI.Our results indicate that adherence to a healthy sleep pattern may attenuate the CVD risk associated with an unfavorable lifestyle.

Certainty about Uncertainty in Sleep Staging; a Theoretical Framework.

Abstract: Sleep stage classification is an important tool for the diagnosis of sleep disorders. Because sleep staging has such a high impact on clinical outcome, it is important that it is done reliably. However, it is known that uncertainty exists in both expert scorers and automated models. On average, agreement between human scorers is only 82.6%. In this manuscript, we provide a theoretical framework to facilitate discussion and further analyses of uncertainty in sleep staging. To this end, we introduce two variants of uncertainty, known from statistics and the machine learning community: aleatoric and epistemic uncertainty. We discuss what these types of uncertainties are, why the distinction is useful, where they arise from in sleep staging, and provide recommendations on how this framework can improve sleep staging in the future.