BookPDF Available
... Intermediate and late chronotypes, but not early chronotypes, obtained more REM sleep during the delayed sleep opportunity than during the normallytimed sleep opportunity. This result suggests intermediate and late chronotypes may have been less impacted by the circadian drive for wake than early chronotypes, as episodes of REM sleep tend to lengthen and dominate sleep prior to full wakening (Carskadon & Dement, 2011;Irwin, 2015) We determined chronotype categories from DLMO, a single circadian measure. ...
Thesis
Full-text available
Chronotype reflects body clock timing. Intuitively, late chronotypes should be less impacted than early chronotypes when working a night shift. However, a series of laboratory studies found early and late chronotypes had similar sleep, cognitive performance, hunger, and snack consumption before and during a single night shift.
... In normal adults, REM sleep increases as the night progress and is longest, in the last third of the sleep episode. As the repetition of sleep episodes progresses, stage 2 gets longer and becomes mostly NREM sleep, while stages 3 and 4 can sometimes disappear completely [27]. ...
Article
Full-text available
Nowadays communication device usage has already reached an unprecedented level. Based on data provided by Central Statistics Agency (BPS), by 2018, at least 62% of Indonesian had a cellphone or a smartphone, and 20% had a computer. Besides smartphones and computers, many Indonesians choose television (TV) as their entertainment device, as proven by 57% of Indonesian households having a TV, although the number has been reduced in the past decade. Based on research conducted by Zickuhr, in 2011, average adults in the United States spent 7-10 hours using their communication device per day, with the most usage in the young adult population (18-35 years) and decreasing as the age increased. The recent development of computer-based communication devices increased our chances of spending much time staring at the blue light emitting screen. Research about the blue light emission effect has become a significant concern, especially in the last five years. It is due to its effect on sleep quality and eyes well-being. This research is an analytic descriptive, non-experiment cross-sectional study. The research uses a prospective and retrospective approach due to the type of data is primary data collected using a questionnaire distributed through social media. Based on Slovin's formula, the sample needed for this study is 133 respondents. This study showed a significant correlation between the usage of blue light-emitting communication devices, sleep quality (P = 0.000), and a moderate relation (r = 0.425) with the positive pattern. Keywords: Communication device usage, blue light, sleeps quality
Article
Full-text available
Graph neural networks have been successfully applied to sleep stage classification, but there are still challenges: (1) How to effectively utilize epoch information of EEG-adjacent channels owing to their different interaction effects. (2) How to extract the most representative features according to confused transitional information in confused stages. (3) How to improve classification accuracy of sleep stages compared with existing models. To address these shortcomings, we propose a multi-layer graph attention network (MGANet). Node-level attention prompts the graph attention convolution and GRU to focus on and differentiate the interaction between channels in the time-frequency domain and the spatial domain, respectively. The multi-head spatial-temporal mechanism balances the channel weights and dynamically adjusts channel features, and a multi-layer graph attention network accurately expresses the spatial sleep information. Moreover, stage-level attention is applied to easily confused sleep stages, which effectively improves the limitations of a graph convolutional network in large-scale graph sleep stages. The experimental results demonstrated classification accuracy; MF1 and Kappa reached 0.825, 0.814, and 0.775 and 0.873, 0.801, and 0.827 for the ISRUC and SHHS datasets, respectively, which showed that MGANet outperformed the state-of-the-art baselines.
Article
Background Mental fatigue is a common and potentially debilitating state that can affect individuals’ health and quality of life. In some cases, its manifestation can precede or mask early signs of other serious mental or physiological conditions. Detecting and assessing mental fatigue can be challenging nowadays as it relies on self-evaluation and rating questionnaires, which are highly influenced by subjective bias. Introducing more objective, quantitative, and sensitive methods to characterize mental fatigue could be critical to improve its management and the understanding of its connection to other clinical conditions. Objective This paper aimed to study the feasibility of using keystroke biometrics for mental fatigue detection during natural typing. As typing involves multiple motor and cognitive processes that are affected by mental fatigue, our hypothesis was that the information captured in keystroke dynamics can offer an interesting mean to characterize users’ mental fatigue in a real-world setting. Methods We apply domain transformation techniques to adapt and transform TypeNet, a state-of-the-art deep neural network, originally intended for user authentication, to generate a network optimized for the fatigue detection task. All experiments were conducted using 3 keystroke databases that comprise different contexts and data collection protocols. Results Our preliminary results showed area under the curve performances ranging between 72.2% and 80% for fatigue versus rested sample classification, which is aligned with previously published models on daily alertness and circadian cycles. This demonstrates the potential of our proposed system to characterize mental fatigue fluctuations via natural typing patterns. Finally, we studied the performance of an active detection approach that leverages the continuous nature of keystroke biometric patterns for the assessment of users’ fatigue in real time. Conclusions Our results suggest that the psychomotor patterns that characterize mental fatigue manifest during natural typing, which can be quantified via automated analysis of users’ daily interaction with their device. These findings represent a step towards the development of a more objective, accessible, and transparent solution to monitor mental fatigue in a real-world environment.
Chapter
There is an abundance of literature and evidence that supports the recent recognition of the importance of sleep over the past few years. Thankfully providers, researchers and public health specialists are all purporting the benefits of good quality sleep for both children and adults. Knowing that poor sleep can have telling consequences on the psychological, developmental and physical health and well-being of children, it is even more important for there to be a keen understanding of basic sleep physiology and pathophysiology. Sleep in young children is dynamic, with the character, pattern and rhythmicity changing as the child moves from infancy into young adulthood. Recognizing these changes can also help to better understand the pathophysiology that can be seen in young and older children alike. This article will review typical presentations of common pediatric sleep disorders, from sleep disordered breathing, sleep related movement disorders as well as parasomnias, insomnia and central disorders of hypersomnolence. Additionally, common diagnostic procedures will be reviewed with first line treatment options discussed. We will explore the behavioral and societal contributions to insomnia in young children and how we can work to counteract or mitigate these effects. Finally, we will touch upon the sleep needs of special populations and the consideration of using supplements and medications to treat sleep insomnia in this population.
Article
This study investigated the effects of air temperature and ventilation on the sleep quality of elderly subjects and elucidated the mechanisms involved. Sixteen subjects aged over 65 years old were exposed to four conditions in a 2 × 2 design: air temperatures of 27°C and 30°C (with a ceiling fan in operation at 30°C) and two ventilation conditions (with and without mechanical ventilation) in experimental bedrooms. Their electroencephalogram, electrooculogram, chin electromyogram, electrocardiogram, respiration, oxygen saturation, and wrist skin temperature were measured continuously during sleep. Saliva samples were collected, and blood pressure was measured both before and after sleep. The results showed that at the temperature of 30°C, the total sleep time, sleep efficiency, and duration of REM sleep of the elderly decreased by 26.3 min, 5.5%, and 5.3 min, respectively, and time awake increased by 27.0 min, in comparison with 27°C, indicating that the sleep quality of the elderly is very vulnerable to heat exposure. Even a small heat load led to an overactive sympathetic nervous system and increased wrist skin temperature, which reduced sleep quality. Improving the ventilation increased the duration of deep sleep and REM sleep by 10.3 min and 3.7 min, respectively. Higher pollutant concentrations affected the respiration and autonomous nervous systems to reduce sleep quality. The benefits of improved thermal environment and ventilation on sleep quality were found to be additive. Good ventilation and the avoidance of raised temperatures in the bedroom are thus both important for the sleep quality of the elderly.
Article
Full-text available
Nightmares are considerably prevalent in the general population and are known to be closely associated with a variety of mental disorders. However, not much is known about the immediate antecedents and consequences of nightmares. Therefore, we used intensive longitudinal assessments to investigate the night‐to‐night within‐person associations between nightmares on the one hand and fear of sleep, somatic as well as cognitive pre‐sleep arousal, and sleep quality on the other hand. Young women with regular nightmares (n = 16) maintained a sleep diary for around 30 days; upon awaking, the participants reported on nightmares and sleep quality during the past night as well as the pre‐sleep levels of arousal and fear of sleep (which resulted in 461 observations). Participants also wore an actigraph, which provided objective sleep parameters. Multilevel modeling showed that higher levels of fear of sleep and lower subjective sleep quality were significantly associated with higher levels of nightmare distress. Furthermore, we found individual differences in the strength of these associations, which implies that factors proximate to nightmares may vary across individuals. Pre‐sleep arousal, however, did not show expected within‐person associations with nightmares or fear of sleep. These findings highlight the crucial role of fear of sleep in the etiology of nightmares and sleep disturbances, while pointing to the importance of pursuing individual, personalised models that explain heterogeneity in the process of triggering nightmares.
Chapter
This paper proposes a novel K-complexes (KCs) detection approach using sleep electroencephalogram (EEG) recordings. A segmentation technique is used to partition an EEG signal into intervals. Then, fast Fourier transform (FFT) is applied to each EEG segment. To find out the most effective input features to represent the EEG signal, the FFT coefficients were investigated. The extracted features are then utilized as the input to an ensemble classifier which is designed using three classifiers: K-means, the Naïve Bayes algorithm and least square support vector machines (LS-SVM). A comparison with existing studies is made and the results showed that the proposed model outperformed state of the art. The proposed approach can be developed as an online system to detect KCs in EEG signals. In addition, it can be applied to other EEG data such as detect sleep apnoea.KeywordsElectroencephalogramK-complexesFast Fourier transformEnsemble classifier
Chapter
Unrecognized sleep disorders can shorten lives, promote hypertension, augment risk for diabetes, exacerbate metabolic syndrome, increase overall medical care costs, impair cognition, cause motor vehicle crashes, reduce workplace productivity, and greatly diminish quality of life. Sleep problems are among the most common complaints that patients bring to their clinicians, but little medical training is devoted to the field and so sleep disorders tend to remain undiagnosed for many years. The case-based chapters in this book highlight key points and pitfalls in a readable, easily assimilated, and memorable format that should improve a clinician's ability to address, investigate, and manage common sleep disorders. The cases illustrate how clinical skill and occasional wisdom can complement data obtained from laboratory testing. Common Pitfalls in Sleep Medicine will be of particular interest to clinicians and trainees in sleep medicine, neurology, internal medicine, family medicine, pulmonary medicine, otolaryngology, psychiatry, and psychology.
Chapter
Unrecognized sleep disorders can shorten lives, promote hypertension, augment risk for diabetes, exacerbate metabolic syndrome, increase overall medical care costs, impair cognition, cause motor vehicle crashes, reduce workplace productivity, and greatly diminish quality of life. Sleep problems are among the most common complaints that patients bring to their clinicians, but little medical training is devoted to the field and so sleep disorders tend to remain undiagnosed for many years. The case-based chapters in this book highlight key points and pitfalls in a readable, easily assimilated, and memorable format that should improve a clinician's ability to address, investigate, and manage common sleep disorders. The cases illustrate how clinical skill and occasional wisdom can complement data obtained from laboratory testing. Common Pitfalls in Sleep Medicine will be of particular interest to clinicians and trainees in sleep medicine, neurology, internal medicine, family medicine, pulmonary medicine, otolaryngology, psychiatry, and psychology.
Article
The sleep patterns of elderly subjects were found to differ from young adult levels with considerable interindividual variability in the older age group. When sleep variables were compared with the individual changes in intellectual function as measured across the 7th through 10th decades of life, a positive correlation was found between time spent in REM sleep and several longitudinal measures of mental functioning. It is suggested that some other factor, perhaps the biological changes occurring in the aging brain, underlies the changes observed here. It is also suggested that sleep changes may be a factor influencing the process of neurobiological aging and senescence.
Article
Genetic and environmental factors affecting sleep patterns have been studied by using surveys, diurnal EEG studies, polysomnographic findings, clinical procedures, and experimental breeding techniques with animals. Each method provides a different level of information regarding both normal sleep patterns and abnormal sleep behavior. Some undeniable hereditary factors have been demonstrated. For the most part, the heritability of sleep related disorders has been a neglected field of study; recent narcolepsy research and the development of animal models of narcolepsy are a notable exception. The animal model, in particular, should prove useful in developing new treatments for sleep disorders and determining their efficacy, side effects, and capability of producing tolerance and addiction.
Article
We combined fMRI and EEG recording to study the neurophysiological responses associated with auditory stimulation across the sleep-wake cycle. We found that presentation of auditory stimuli produces bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and nonrapid eye movement (NREM) sleep. However, the left parietal and, bilaterally, the prefrontal and cingulate cortices and the thalamus were less activated during NREM sleep compared to wakefulness. These areas may play a role in the further processing of sensory information required to achieve conscious perception during wakefulness. Finally, during NREM sleep, the left amygdala and the left prefrontal cortex were more activated by stimuli having special affective significance than by neutral stimuli. These data suggests that the sleeping brain can process auditory stimuli and detect meaningful events.
Book
1. Introduction.- 1.1 Beyond Time.- 1.2 The Rosetta Stone.- 1.3 Overview.- 2. Experimental Background.- 2.1 Phenomena and Terminology.- 2.2 History of Free-Run Studies.- 3. Data Bank.- 3.1 Subject 1.- 3.2 Subject 2.- 3.3 Subject 3.- 3.4 Subject 4.- 3.5 Subject 5.- 3.6 Subject 6.- 3.7 Subject 7.- 3.8 Subject 8.- 3.9 Subject 9.- 3.10 Subject 10.- 3.11 Subject 11.- 3.12 Subject 12.- 3.13 Subject 13.- 3.14 Subject 14.- 3.15 Subject 15.- 3.16 Subject 16.- 3.17 Subject 17.- 3.18 Subject 18.- 3.19 Subject 19.- 3.20 Subject 20.- 3.21 Subject 21.- 3.22 Subject 22.- 4. Patterns.- 4.1 Durations Vary with Circadian Phase of Sleep Onset.- 4.2 Sleep Length and Prior Wake Length.- 4.3 Timing of Wake-Up.- 4.4 Timing of Sleep Onset.- 4.5 Wake-Maintenance Zones.- 4.6 Estimating Circadian Parameters from Sleep Data Alone.- 4.7 Phase-Trapping.- 4.8 Slow Changes in Sleep-Wake Cycle Length.- 4.9 Miscellany and Missing Patterns.- 4.10 Napping and Split Sleep.- 4.11 Summary: The Basic Patterns of Internal Desynchrony.- 5. Theoretical Background.- 5.1 Conceptual Model of Aschoff and Wever.- 5.2 Wever's Noninteractive Model.- 5.3 Kronauer's XY Model: Coupled Van der Pol Oscillators.- 5.4 Conceptual Model of Borbely.- 5.5 Winfree's Half-Model.- 5.6 Gated Pacemaker of Daan, Beersma, and Borbely.- 5.7 Other Approaches.- 6. Analysis of Models.- 6.1 Introduction.- 6.2 BEATS Model.- 6.3 PHASE Model.- 6.4 XY Model of Kronauer et al..- 6.5 Model of Daan et al..- 7. Simulations.- 7.1 Transition from Synchrony to Desynchrony.- 7.2 Napping and Split Sleep Simulations.- 7.3 A Representative Simulation of Internal Desynchrony.- 7.4 Overall Performance During Desynchrony.- 7.5 Summary and Discussion.- 8. Epilogue.- 8.1 Contributions.- 8.2 Directions for Future Research.- References.- Index of Authors.
Article
To compare the new American Academy of Sleep Medicine (AASM) criteria for scoring sleep with the previous Rechtschaffen and Kales (R&K) criteria in a cohort of children with primary snoring, obstructive sleep apnea syndrome (OSAS) and normal controls. Polysomnography was performed in 26 consecutive children with primary snoring (13 males, mean age 6.2 years, SD 3.2), in 39 with OSAS (24 males, mean age 6.1 years, SD 3.0), and in 10 age-matched normal controls. Compared to the other groups, OSAS children showed a lower percentage of slow-wave sleep, using both R&K and AASM criteria; they also showed a higher percentage of stage shifts, and N1, using the AASM criteria. Children with primary snoring showed a higher percentage of N1, compared to controls. These results indicate that the use of the new AASM criteria seem to disclose more differences in sleep parameters than the R&K rules in children with OSAS. The AASM criteria seem to disclose a high degree of sleep fragmentation in children with OSAS, mostly related to the repeated occurrence of N1.