scispace - formally typeset
Search or ask a question

Showing papers on "Sleep (system call) published in 2021"


Journal ArticleDOI
TL;DR: In this article, the impact of home confinement during the COVID-19 pandemic on sleep patterns and sleep disturbances in Italian children and adolescents was examined, and the authors found a significant delay in bedtime and risetime in all age groups and adolescents experienced the most significant delay: weekday bedtime ≥23 was reported by 284% of 6- to 12-year old children during lockdown vs 09% before and by 635% vs 123% of 13- to 18-year-old adolescents.

88 citations


Journal ArticleDOI
TL;DR: The authors summarizes the known associations between COVID-19 and sleep dysfunction, including insomnia, excessive daytime sleepiness, restless legs syndrome and nightmares, and touches upon pandemic-related considerations for obstructive sleep apnea and continuous positive airway pressure treatment.

56 citations


Journal ArticleDOI
TL;DR: This paper proposes a low-cost and non-intrusive sleep monitoring system using commodity Wi-Fi devices, namely WiFi-Sleep, and introduces a deep learning method combined with clinical sleep medicine prior knowledge to achieve four-stage sleep monitoring with limited data sources.
Abstract: Sleep monitoring is essential to people’s health and wellbeing, which can also assist in the diagnosis and treatment of sleep disorder. Compared with contact-based solutions, contactless sleep monitoring does not attach any device to the human body; hence, it has attracted increasing attention in recent years. Inspired by the recent advances in Wi-Fi-based sensing, this article proposes a low-cost and nonintrusive sleep monitoring system using commodity Wi-Fi devices, namely, WiFi-Sleep. We leverage the fine-grained channel state information from multiple antennas and propose advanced fusion and signal processing methods to extract accurate respiration and body movement information. We introduce a deep learning method combined with clinical sleep medicine prior knowledge to achieve four-stage sleep monitoring with limited data sources (i.e., only respiration and body movement information). We benchmark the performance of WiFi-Sleep with polysomnography, the gold reference standard. Results show that WiFi-Sleep achieves an accuracy of 81.8%, which is comparable to the state-of-the-art sleep stage monitoring using expensive radar devices.

40 citations


Journal ArticleDOI
TL;DR: In this article, the authors provided an updated overview of the impact of the COVID-19 pandemic on circadian rhythms and sleep based on the results of published studies (n = 48) in three sections.

33 citations


Journal ArticleDOI
TL;DR: This work proposes better technique that can be designed to discriminate the stages of sleep which can help physicians to do an analysis and examination of related sleep disorders.
Abstract: Recently, sleep disorder is taken as a serious issue in people living. Normally people cerebrum passes through variety of static physiological steps or changes for the duration of sleep. Biomedical signal such as EEG, ECG, EOG and EMG setup and signals used to recognize sleep disorders. This work proposes better technique that can be designed to discriminate the stages of sleep which can help physicians to do an analysis and examination of related sleep disorders. In order to identify a modification inside brain, EEG signal partitioned with 5 frequency bands: delta, theta, alpha, beta and gamma. After signal acquisition, Band pass filter is applied to discriminate the input EEG signal of Fpz–Cz electrodes into frequency bands. Statistical specific features are extracted from distinctiveness impression of EEG signal. Then classification is required for classifying the sleep stages automatically with fuzzy kernel support vector machine and simple recurrent network (SRN). In SRN, statistical features were extracted and allocate 30 s period to 5 possible levels in sleep; wakefulness, Non Rapid Eye Movement Sleep Stage 1 (NREMSS 1), NREMSS 2, NREMSS 3 and NREMSS 4, Rapid Eye Movement Sleep Stage (REMSS). These signal acquired from sleep-EDF repository from PhysioBank (PB) used to validate our proposed scheme. Simple recurrent network classification performance rate is found as 90.2% than that of other new classifiers such as feed forward neural network (FNN) and probabilistic neural network (PNN) next it was compared and results are experimented in proposed work.

23 citations


Journal ArticleDOI
07 Jan 2021-Sensors
TL;DR: In this paper, a nanomaterial galvanic skin response (GSR) sensor, printed on a soft elastomeric membrane, can have intimate contact with the skin to reduce motion artifact during sleep.
Abstract: Sleep is an essential element to human life, restoring the brain and body from accumulated fatigue from daily activities. Quantitative monitoring of daily sleep quality can provide critical feedback to evaluate human health and life patterns. However, the existing sleep assessment system using polysomnography is not available for a home sleep evaluation, while it requires multiple sensors, tabletop electronics, and sleep specialists. More importantly, the mandatory sleep in a designated lab facility disrupts a subject’s regular sleep pattern, which does not capture one’s everyday sleep behaviors. Recent studies report that galvanic skin response (GSR) measured on the skin can be one indicator to evaluate the sleep quality daily at home. However, the available GSR detection devices require rigid sensors wrapped on fingers along with separate electronic components for data acquisition, which can interrupt the normal sleep conditions. Here, we report a new class of materials, sensors, electronics, and packaging technologies to develop a wireless, soft electronic system that can measure GSR on the wrist. The single device platform that avoids wires, rigid sensors, and straps offers the maximum comfort to wear on the skin and minimize disruption of a subject’s sleep. A nanomaterial GSR sensor, printed on a soft elastomeric membrane, can have intimate contact with the skin to reduce motion artifact during sleep. A multi-layered flexible circuit mounted on top of the sensor provides a wireless, continuous, real-time recording of GSR to classify sleep stages, validated by the direct comparison with the standard method that measures other physiological signals. Collectively, the soft bioelectronic system shows great potential to be working as a portable, at-home sensor system for assessing sleep quality before a hospital visit.

21 citations


Journal ArticleDOI
26 Apr 2021-PLOS ONE
TL;DR: In this paper, the authors examined the impact of social-distancing directives to contain community transmission of the COVID-19 virus can be expected to affect sleep timing, duration or quality.
Abstract: Social-distancing directives to contain community transmission of the COVID-19 virus can be expected to affect sleep timing, duration or quality. Remote work or school may increase time available for sleep, with benefits for immune function and mental health, particularly in those individuals who obtain less sleep than age-adjusted recommendations. Young adults are thought to regularly carry significant sleep debt related in part to misalignment between endogenous circadian clock time and social time. We examined the impact of social-distancing measures on sleep in young adults by comparing sleep self-studies submitted by students enrolled in a university course during the 2020 summer session (entirely remote instruction, N = 80) with self-studies submitted by students enrolled in the same course during previous summer semesters (on-campus instruction, N = 452; cross-sectional study design). Self-studies included 2-8 week sleep diaries, two chronotype questionnaires, written reports, and sleep tracker (Fitbit) data from a subsample. Students in the 2020 remote instruction semester slept later, less efficiently, less at night and more in the day, but did not sleep more overall despite online, asynchronous classes and ~44% fewer work days compared to students in previous summers. Subjectively, the net impact on sleep was judged as positive or negative in equal numbers of students, with students identifying as evening types significantly more likely to report a positive impact, and morning types a negative impact. Several features of the data suggest that the average amount of sleep reported by students in this summer course, historically and during the 2020 remote school semester, represents a homeostatic balance, rather than a chronic deficit. Regardless of the interpretation, the results provide additional evidence that social-distancing measures affect sleep in heterogeneous ways.

20 citations


Journal ArticleDOI
TL;DR: A systematic review on sleep bruxism (SB) as a comorbid condition of other sleep-related disorders is presented in this paper, where the authors aim to determine the associations between SB and other sleep related disorders, and to explain the underlying mechanisms of these associations.

19 citations


Journal ArticleDOI
TL;DR: In this article, the impact of the COVID-19 outbreak on sleep of participants with autism spectrum disorder (ASD) was assessed, and the effect of sleep deprivation on participants with ASD was investigated.
Abstract: Study Objectives: The impact of the COVID-19 outbreak on sleep of participants with autism spectrum disorder (ASD) was assessed. Methods: Parents of 111 children and adolescents with ASD filled out...

19 citations


Journal ArticleDOI
TL;DR: In this paper, a cross-sectional web-based study using an online survey made available for dyads of parents and their children during the 7th week of quarantine in southern Brazil was conducted.
Abstract: OBJECTIVE: To evaluate sleep characteristics of parents and their children during the COVID-19 pandemic and predictors for sleep disturbances. METHODS: Cross-sectional web-based study using an online survey made available for dyads of parents and their children during the 7th week of quarantine in southern Brazil. Parents' and adolescents' sleep were characterized using the Pittsburgh Sleep Quality Index and the Epworth Sleepiness Scale. For children aged 0-3 years parents completed the Brief Infant Sleep Questionnaire, for those aged 4-12 years the Sleep Disturbance Scale for Children. Parents also informed, subjectively, their perception about sleep habits during social distancing. Multiple regression was run to predict sleep disturbances in adults using independent variables: sex, income, education, children age, and children with sleep disturbances. RESULTS: Data from 577 dyads showed sleep alterations in 69,8% of adults, in 58,6% of children aged 0-3 years, 33,9% in the 4-12 years range (with a predominance of disorders of initiating or maintaining sleep), and 56,6% in adolescents. Sex (female) and children with sleep disturbances were significant predictors of a sleep problem in parents (p < 0.005). Subjective perception revealed complaints related to emotional concerns such as anxiety and fear in adults and due to alterations in routine in children and adolescents. CONCLUSION: The present study's data showed an increased rate of sleep problems among families during quarantine both measured by validated instruments and also based on personal perception.

18 citations


Journal ArticleDOI
TL;DR: In this article, the authors validate a contactless monitoring system on eight patients with a high likelihood of relevant obstructive sleep apnea, which are enrolled for a sleep study at a specialized sleep center.
Abstract: Polysomnography (PSG) is the current gold standard for the diagnosis of sleep disorders. However, this multi-parametric sleep monitoring tool also has some drawbacks, e.g. it limits the patient's mobility during the night and it requires the patient to come to a specialized sleep clinic or hospital to attach the sensors. Unobtrusive techniques for the detection of sleep disorders such as sleep apnea are therefore gaining increasing interest. Remote photoplethysmography using video is a technique which enables contactless detection of hemodynamic information. Promising results in near-infrared have been reported for the monitoring of sleep-relevant physiological parameters pulse rate, respiration and blood oxygen saturation. In this study we validate a contactless monitoring system on eight patients with a high likelihood of relevant obstructive sleep apnea, which are enrolled for a sleep study at a specialized sleep center. The dataset includes 46.5 hours of video recordings, full polysomnography and metadata. The camera can detect pulse and respiratory rate within 2 beats/breaths per minute accuracy 92% and 91% of the time, respectively. Estimated blood oxygen values are within 4 percentage points of the finger-oximeter 89% of the time. These results demonstrate the potential of a camera as a convenient diagnostic tool for sleep apnea, and sleep disorders in general.

Journal ArticleDOI
TL;DR: In this article, the probabilities of momentary sleep stages, represented as hypnodensity graphs and then computing vectorial cross-correlations of different EEG channels, were determined.

Journal ArticleDOI
TL;DR: Recently, a key molecular mechanism that allows broad synaptic weakening during sleep was identified and other mechanisms still being investigated should eventually explain how sleep can weaken most synapses but afford protection to some, including those directly activated by learning as discussed by the authors.

Journal ArticleDOI
27 Jul 2021-Sensors
TL;DR: In this paper, the authors provide context surrounding the complex hardware and software developed by wearable device companies in their attempts to estimate sleep-related phenomena, and outlines considerations and contributing factors for overall device success.
Abstract: Despite prolific demands and sales, commercial sleep assessment is primarily limited by the inability to "measure" sleep itself; rather, secondary physiological signals are captured, combined, and subsequently classified as sleep or a specific sleep state. Using markedly different approaches compared with gold-standard polysomnography, wearable companies purporting to measure sleep have rapidly developed during recent decades. These devices are advertised to monitor sleep via sensors such as accelerometers, electrocardiography, photoplethysmography, and temperature, alone or in combination, to estimate sleep stage based upon physiological patterns. However, without regulatory oversight, this market has historically manufactured products of poor accuracy, and rarely with third-party validation. Specifically, these devices vary in their capacities to capture a signal of interest, process the signal, perform physiological calculations, and ultimately classify a state (sleep vs. wake) or sleep stage during a given time domain. Device performance depends largely on success in all the aforementioned requirements. Thus, this review provides context surrounding the complex hardware and software developed by wearable device companies in their attempts to estimate sleep-related phenomena, and outlines considerations and contributing factors for overall device success.

Journal ArticleDOI
TL;DR: In this article, the limits to sleep monitoring quality within this spatial constraint were determined, and it was shown that if large electrode distances are used, positioning is not critical for achieving large sleep-related signal-to-noise-ratio.
Abstract: Modern sleep monitoring development is shifting towards the use of unobtrusive sensors combined with algorithms for automatic sleep scoring. Many different combinations of wet and dry electrodes, ear-centered, forehead-mounted or headband-inspired designs have been proposed, alongside an ever growing variety of machine learning algorithms for automatic sleep scoring. Objective: Among candidate positions, those in the facial area and around the ears have the benefit of being relatively hairless, and in our view deserve extra attention. In this paper, we seek to determine the limits to sleep monitoring quality within this spatial constraint. Methods: We compare 13 different, realistic sensor setups derived from the same data set and analysed with the same pipeline. Results: All setups which include both a lateral and an EOG derivation show similar, state-of-the-art performance, with average Cohen's kappa values of at least 0.80. Conclusion: If large electrode distances are used, positioning is not critical for achieving large sleep-related signal-to-noise-ratio, and hence accurate sleep scoring. Significance: We argue that with the current competitive performance of automated staging approaches, there is a need for establishing an improved benchmark beyond current single human rater scoring.

Journal ArticleDOI
TL;DR: How few worksites reported offering sleep-focused programs for their employees is highlighted, and those worksites that did feature such programs, were commonly well-resourced and had senior leadership support for WHPP initiatives in general.
Abstract: Background:Poor sleep health, including sleep deficiency and sleep disturbance, is common among employed adults in the U.S. and is associated with undesirable workplace outcomes. Adoption of workpl...

Journal ArticleDOI
TL;DR: A review of the current understanding of the circadian regulation of sleep can be found in this paper, where the authors discuss the neural circuitry and molecular mechanisms underlying daily sleep timing, and the trajectory of circadian regulation across development.

Journal ArticleDOI
TL;DR: In this article, a correlational cross-sectional study was conducted to assess sleep quality of Tunisian medical students during home confinement due to the COVID-19 pandemic, and to analyze the relationship between sleep quality and sociodemographic, clinical, confinement-related and psychological variables.
Abstract: Objectives We aimed to assess sleep quality of Tunisian medical students during home confinement due to the COVID-19 pandemic, and to analyze the relationship between sleep quality and sociodemographic, clinical, confinement-related and psychological variables. Methods A correlational cross-sectional study was conducted from April 11th to May 3rd 2020. Medical students who have been in home confinement and who accepted to participate in an online survey were targeted. Sociodemographic data, clinical variables, and data related to home confinement were collected. Participants also completed Pittsburgh Sleep Quality Index, Depression, Anxiety and Stress Scale and Beck Hopelessness Scale. Results Results showed a high prevalence of poor sleepers among medical students (72.5%) with poor subjective sleep quality, increased sleep latency, sleep disturbances and daytime dysfunction. Multiple regression analysis revealed that family history of suicide attempts, tobacco use, perception of home confinement and reduced physical activity during home confinement significantly contributed to poor sleep quality. Among the psychological variables, anxiety and hopelessness significantly contributed to poor sleep quality in medical students during home confinement. Conclusions Results revealed a high prevalence of poor sleep quality in medical students who have been in home confinement due to the COVID-19 pandemic. Except family history of suicide attempts, factors that significantly contributed to poor sleep quality were modifiable factors. Sleep quality and sleep parameters need to be assessed in this particular population and adequate measures aiming to promote quality of sleep need to be enhanced, given the crucial regenerative, homeostatic and psychological roles of sleep.

Journal ArticleDOI
TL;DR: A bed-mounted vibration sensor-based system to monitor vital parameters during sleep, including heartbeat rate (HR) and respiratory rate (RR), body movements and sleep postures, and algorithms for body movement and sleep posture identification are proposed based on vibration signal features.
Abstract: In this paper, a bed-mounted vibration sensor-based system is proposed to monitor vital parameters during sleep, including heartbeat rate (HR) and respiratory rate (RR), body movements and sleep postures. Our system enables smart healthcare that monitors daily sleep in a ubiquitous and non-invasive manner. Besides, the system is contact-free, as no external wearable devices and physical contacts are required. Furthermore, the vibration-based approach also avoids the privacy violation caused by the usage of surveillance cameras. To effectively monitor sleep status, a robust stable signal mode decomposition based HR and RR estimation method is developed for the complicated and noisy vibration signals. Besides, algorithms for body movement and sleep posture identification are also proposed based on vibration signal features. A prototype system is demonstrated with system details, showing great potentials in monitoring sleep status in a real-time user-friendly manner. Experimental results of short term and long term experiments with different participants and beds show that our system achieves satisfying accuracy compared with dedicated commercial devices.

Journal ArticleDOI
TL;DR: In this paper, the authors investigated Ontario adults' reported sleep quantity, quality, and disturbances during the early months of the COVID-19 pandemic (April-July 2020).

Journal ArticleDOI
TL;DR: In this paper, the authors examined the impact of travel restrictions and work from home orders imposed in Ireland in March 2020 on sleep timing and quality, and found a significant shift to later sleep start and end times, as well as delayed time of midsleep on both work and free days, during the period of restrictions.

Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors investigated the sleep quality and changes in sleep patterns before and during the outbreak in the general population in China and to determine factors related to sleep quality.

Journal ArticleDOI
TL;DR: In this paper, an Internet of Things-based real-time sleep apnea monitoring system has been developed, which allows the user to measure different indexes of sleep and will notify them through a mobile application when anything odd occurs.
Abstract: Sleep is an essential and vital element of a person’s life and health that helps to refresh and recharge the mind and body of a person. The quality of sleep is very important in every person’s lifestyle, removing various diseases. Bad sleep is a big problem for a lot of people for a very long time. People suffering from various diseases are dealing with various sleeping disorders, commonly known as sleep apnea. A lot of people die during sleep because of uneven body changes in the body during sleep. On that note, a system to monitor sleep is very important. Most of the previous systems to monitor sleeping problems cannot deal with the real time sleeping problem, generating data after a certain period of sleep. Real-time monitoring of sleep is the key to detecting sleep apnea. To solve this problem, an Internet of Things- (IoT-) based real-time sleep apnea monitoring system has been developed. It will allow the user to measure different indexes of sleep and will notify them through a mobile application when anything odd occurs. The system contains various sensors to measure the electrocardiogram (ECG), heart rate, pulse rate, skin response, and SpO2 of any person during the entire sleeping period. This research is very useful as it can measure the indexes of sleep without disturbing the person and can also show it in the mobile application simultaneously with the help of a Bluetooth module. The system has been developed in such a way that it can be used by every kind of person. Multiple analog sensors are used with the Arduino UNO to measure different parameters of the sleep factor. The system was examined and tested on different people’s bodies. To analyze and detect sleep apnea in real-time, the system monitors several people during the sleeping period. The results are displayed on the monitor of the Arduino boards and in the mobile application. The analysis of the achieved data can detect sleep apnea in some of the people that the system monitored, and it can also display the reason why sleep apnea happens. This research also analyzes the people who are not in the danger of sleeping problems by the achieved data. This paper will help everyone learn about sleep apnea and will help people detect it and take the necessary steps to prevent it.

Journal ArticleDOI
TL;DR: Findings demonstrate unique associations between disparate sleep disturbance and reward responsiveness elements, highlighting new treatment mechanisms for anhedonia and depression.

Journal ArticleDOI
TL;DR: In this article, a standard definition of sleep quality has not been identified, and polysomnography (PSG) provides important information for sleep quality assessment, but it is not suitable for medical applications.
Abstract: Study Objectives:Sleep is one of the most common factors related to health, yet a standard definition of sleep quality has not been identified. Polysomnography (PSG) provides important information ...

Journal ArticleDOI
TL;DR: Assessment of take-over behavior immediately after sleep and driving behavior during the 10 min after sleep suggest that human-machine interaction design should account for the drivers' impaired post-sleep driving performance.

Proceedings ArticleDOI
21 Jan 2021
TL;DR: This novel system has high efficiency as an alternative not only to monitor sleep but also to identify and treat abnormal breathing patterns by training to sleep on your side positions, which can help improve the quality of sleep and reduce snoring and sleep apnea.
Abstract: Obstructive sleep apnea (OSA) is the essential cause of sleep-related breathing disorders in which breathing repeatedly stops and starts during sleep. Sleep-disordered breathing can affect our overall health, safety, and quality of life. This study was focused on the detection of sleep posture and sleep breathing disorder, by measuring the sensing response of a piezoelectric sensor installed on the mattress, pillowcase, and sleep apnea positional-therapy device. In this work, we have developed a sleep monitoring system based on an unobtrusive method. The results of sleep efficiency, sleep pose, and sleep apnea was compared with the gold standard of sleep monitoring in-laboratory polysomnography (PSG). Linear regression of all results reveals strong correlations between our smart sleep system and the PSG device. This novel system has high efficiency as an alternative not only to monitor sleep but also to identify and treat abnormal breathing patterns by training to sleep on your side positions. It can help improve the quality of sleep and reduce snoring and sleep apnea.

Journal ArticleDOI
TL;DR: In this paper, the authors evaluated the impact of the COVID-19 pandemic on insomnia and other sleep disturbances in health care professionals using a survey distributed using social media and organizat...
Abstract: Study Objectives:To evaluate the impact of COVID-19 pandemic on insomnia and other sleep disturbances in health care professionals. Methods:A survey was distributed using social media and organizat...

Journal ArticleDOI
TL;DR: A meta-analysis has estimated the prevalence of self-reported sleep disturbances in people living with HIV to be 58%, with commonly identified disturbances including insomnia, obstructive sleep apnoea and poor sleep quality as mentioned in this paper.

Journal ArticleDOI
TL;DR: In this article, the prevalence of sleep disturbances among 6-12-year-old children during the COVID-19 pandemic in Turkey was 55.5% and most common sleep disturbances were bedtime resistance, sleep onset delay, and sleep duration.