921 resultados para Sleep EEG


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Aim: The aim was to investigate whether the sleep practices in early childhood education (ECE) settings align with current evidence on optimal practice to support sleep. Background: Internationally, scheduled sleep times are a common feature of daily schedules in ECE settings, yet little is known about the degree to which care practices in these settings align with the evidence regarding appropriate support of sleep. Methods: Observations were conducted in 130 Australian ECE rooms attended by preschool children (Mean = 4.9 years). Of these rooms, 118 had daily scheduled sleep times. Observed practices were scored against an optimality index, the Sleep Environment and Practices Optimality Score, developed with reference to current evidence regarding sleep scheduling, routines, environmental stimuli, and emotional climate. Cluster analysis was applied to identify patterns and prevalence of care practices in the sleep time. Results: Three sleep practices types were identified. Supportive rooms (36%) engaged in practices that maintained regular schedules, promoted routine, reduced environmental stimulation, and maintained positive emotional climate. The majority of ECE rooms (64%), although offering opportunity for sleep, did not engage in supportive practices: Ambivalent rooms (45%) were emotionally positive but did not support sleep; Unsupportive rooms (19%) were both emotionally negative and unsupportive in their practices. Conclusions: Although ECE rooms schedule sleep time, many do not adopt practices that are supportive of sleep. Our results underscore the need for education about sleep supporting practice and research to ascertain the impact of sleep practices in ECE settings on children’s sleep health and broader well-being.

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Objective To examine mean level differences, and longitudinal and reciprocal relations among behavioral sleep problems, emotional dysregulation, and attentional regulation across early childhood for children with and without ADHD at 8-9 years. Method This study used data from Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) – Infant Cohort (n = 4109 analyzed). Children with and without ADHD were identified at age 8-9 years via parent-report of ADHD diagnosis and the 5-item Inattention-Hyperactivity subscale from the Strengths and Difficulties Questionnaire. Maternal report of child sleep problems and self-regulation was collected at 0-1, 2-3, 4-5 and 6-7 years of age. ANOVA was used to compare mean level differences in sleep problems, emotional and attentional regulation by ADHD group. Longitudinal structural equation modeling examined the relations among sleep and self-regulation across time in children with and without ADHD. Results Children with ADHD had persistently elevated levels of sleep problems (from infancy) and emotional and attentional dysregulation compared to controls (from 2-3 years of age). Sleep problems, emotional dysregulation, and attentional regulation were stable over time for both groups. Sleep problems were associated with greater emotional dysregulation two years later from 2-3 years of age for both groups, which in turn was associated with poorer attentional regulation. There was no direct relationship between sleep problems and later attentional regulation. Conclusion Sleep problems in children with and without ADHD are associated with emotional dysregulation, which in turn contributes to poorer attentional functioning. This study highlights the importance of assessing and managing sleep problems in young children.

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Background Children’s sleep problems and self-regulation problems have been independently associated with poorer adjustment to school, but there has been limited exploration of longitudinal early childhood profiles that include both indicators. Aims This study explores the normative developmental pathway for sleep problems and self-regulation across early childhood, and investigates whether departure from the normative pathway is associated with later social-emotional adjustment to school. Sample This study involved 2880 children participating in the Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) – Infant Cohort from Wave 1 (0-1 years) to Wave 4 (6-7 years). Method Mothers reported on children’s sleep problems, emotional, and attentional self-regulation at three time points from birth to 5 years. Teachers reported on children’s social-emotional adjustment to school at 6-7 years. Latent profile analysis was used to establish person-centred longitudinal profiles. Results Three profiles were found. The normative profile (69%) had consistently average or higher emotional and attentional regulation scores and sleep problems that steadily reduced from birth to 5. The remaining 31% of children were members of two non-normative self-regulation profiles, both characterised by escalating sleep problems across early childhood and below mean self-regulation. Non-normative group membership was associated with higher teacher-reported hyperactivity and emotional problems, and poorer classroom self-regulation and prosocial skills. Conclusion Early childhood profiles of self-regulation that include sleep problems offer a way to identify children at risk of poor school adjustment. Children with escalating early childhood sleep problems should be considered an important target group for school transition interventions.

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- Introduction Heat-based training (HT) is becoming increasingly popular as a means of inducing acclimation before athletic competition in hot conditions and/or to augment the training impulse beyond that achieved in thermo-neutral conditions. Importantly, current understanding of the effects of HT on regenerative processes such as sleep and the interactions with common recovery interventions remain unknown. This study aimed to examine sleep characteristics during five consecutive days of training in the heat with the inclusion of cold-water immersion (CWI) compared to baseline sleep patterns. - Methods Thirty recreationally-trained males completed HT in 32 ± 1 °C and 60% rh for five consecutive days. Conditions included: 1) 90 min cycling at 40 % power at VO2max (Pmax) (90CONT; n = 10); 90 min cycling at 40 % Pmax with a 20 min CWI (14 ± 1 °C; 90CWI; n = 10); and 30 min cycling alternating between 40 and 70 % Pmax every 3 min, with no recovery intervention (30HIT; n = 10). Sleep quality and quantity was assessed during HT and four nights of 'baseline' sleep (BASE). Actigraphy provided measures of time in and out of bed, sleep latency, efficiency, total time in bed and total time asleep, wake after sleep onset, number of awakenings, and wakening duration. Subjective ratings of sleep were also recorded using a 1-5 Likert scale. Repeated measures analysis of variance (ANOVA) was completed to determine effect of time and condition on sleep quality and quantity. Cohen's d effect sizes were also applied to determine magnitude and trends in the data. - Results Sleep latency, efficiency, total time in bed and number of awakenings were not significantly different between BASE and HT (P > 0.05). However, total time asleep was significantly reduced (P = 0.01; d = 1.46) and the duration periods of wakefulness after sleep onset was significantly greater during HT compared with BASE (P = 0.001; d = 1.14). Comparison between training groups showed latency was significantly higher for the 30HIT group compared to 90CONT (P = 0.02; d = 1.33). Nevertheless, there were no differences between training groups for sleep efficiency, total time in bed or asleep, wake after sleep onset, number of awakenings or awake duration (P > 0.05). Further, cold-water immersion recovery had no significant effect on sleep characteristics (P > 0.05). - Discussion Sleep plays an important role in athletic recovery and has previously been demonstrated to be influenced by both exercise training and thermal strain. Present data highlight the effect of HT on reduced sleep quality, specifically reducing total time asleep due to longer duration awake during awakenings after sleep onset. Importantly, although cold water recovery accelerates the removal of thermal load, this intervention did not blunt the negative effects of HT on sleep characteristics. - Conclusion Training in hot conditions may reduce both sleep quantity and quality and should be taken into consideration when administering this training intervention in the field.

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In recent years a variety of mobile apps, wearable technologies and embedded systems have emerged that allow individuals to track the amount and the quality of their sleep in their own beds. Despite the widespread adoption of these technologies, little is known about the challenges that current users face in tracking and analysing their sleep. Hence we conducted a qualitative study to examine the practices of current users of sleep tracking technologies and to identify challenges in current practice. Based on data collected from 5 online forums for users of sleep-tracking technologies, we identified 22 different challenges under the following 4 themes: tracking continuity, trust, data manipulation, and data interpretation. Based on these results, we propose 6 design opportunities to assist researchers and practitioners in designing sleep-tracking technologies.

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One of the most important applications of adaptive systems is in noise cancellation using adaptive filters. Ln this paper, we propose adaptive noise cancellation schemes for the enhancement of EEG signals in the presence of EOG artifacts. The effect of two reference inputs is studied on simulated as well as recorded EEG signals and it is found that one reference input is enough to get sufficient minimization of EOG artifacts. This has been verified through correlation analysis also. We use signal to noise ratio and linear prediction spectra, along with time plots, for comparing the performance of the proposed schemes for minimizing EOG artifacts from contaminated EEG signals. Results show that the proposed schemes are very effective (especially the one which employs Newton's method) in minimizing the EOG artifacts from contaminated EEG signals.

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Migraine is a common disease in children and adolescents, affecting roughly 10% of school-aged children. Recent studies have revealed an increasing incidence of childhood migraine, but migraine remains an underrecognized and undertreated condition in the pediatric population. Migraine attacks are painful and disabling and can affect a child´s life in many ways. Effective drug treatment is usually needed. The new migraine drugs, triptans, were introduced at the beginning of the 1990s and have since been shown to be very effective in the treatment of migraine attacks in adults. Although they are widely used in adults, the acute treatment of migraine in children and adolescents is still based on paracetamol and nonsteroidal anti-inflammatory drugs. Some children can control their attacks satisfactorily with simple analgesics, but at least one-third need more powerful treatments. When this thesis work commenced, hardly any information existed on the efficacy and safety of triptans in children. The study aim of the thesis was to identify more efficient treatments of migraine for children and adolescents by investigating the efficacy of sumatriptan nasal spray and oral rizatriptan compared with placebo in them. Sleep has an impact on migraine in many aspects. Despite the clinical relevance and common manifestation of sleep in the context of migraine in children, very little research data on the true frequency of sleep exist. As sleeping is so often related to childhood migraine, it can be a confounding factor in clinical drug trials of migraine treatments in children and adolescents. How the results of a sleeping child should be analyzed is under continual debate. The aim of the thesis was also to clarify this as well as to evaluate the frequency of sleeping during migraine attacks in children and factors affecting frequency. Both nasal sumatriptan and oral rizatriptan were effective (superior to placebo), and well tolerated in treatment of migraine attacks in children and adolescents aged 8-17 and 6-17 years, respectively. No serous adverse effects were observed. The results of this work suggest that nasal sumatriptan 20 mg and rizatriptan 10 mg can be effectively and safely used to treat migraine attacks in adolescents aged over 12 years if more effective drugs than NSAIDs are needed. No difference was observed in efficacy or safety of nasal sumatriptan and rizatriptan between children aged younger than 12 years and older children, but because the treated number of patients under 12 years is still small, more studies are needed before sumatriptan or rizatriptan can be recommended for use in this population. Sleeping during migraine attacks was very common, and most children at least occasionally slept during an attack. Falling asleep was especially common in children under eight years of age and during the first hour after the onset of attack. Children who were able to sleep soon after attack onset were more likely pain-free at two hours. Sleeping probably both improves recovery from a migraine attack and is a sign of headache relief. Falling asleep should be classified as a sign of headache relief in clinical drug trials when studying migraine treatments in children and adolescents.

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Background The most common pathway to development of diabetes foot ulcers is repetitive daily activity stress on the plantar surface of the neuropathic foot. Studies suggest an association between different diabetic foot complications and physical activity. However, to the best of the authors knowledge the steps/day and sleep patterns of people with diabetic foot ulcers has yet to be investigated. This observational study aims to investigate the physical activity and sleep patterns of three groups of adults with type 2 diabetes and different foot complications Methods Participants with type 2 diabetes were recruited into three groups: 1. those with no reported foot complications (DNIL), 2. those with diagnosis of neuropathy (DPN) and 3. those with a neuropathic ulcer (DFU). Exclusion criteria included peripheral arterial disease and mobility aid use. Participants wore a SenseWear Pro 3 Armband continuously for 7 days and completed an Epworth Sleepiness Scale. The Armband is a validated automated measure of activity (walking steps, average Metabolic Equivalent Task (MET), physical activity (>3 METs) duration), energy expenditure(kJ) (total and physical activity (>3 METs)) and sleep (duration). Data on age, sex, BMI, diabetes duration and HbA1c were also collected. Results Sixty-Six (14 DNIL, 22 DPN and 30 DFU's participants were recruited; 71% males, mean age 61(±12) years, diabetes duration 13(±9) years, HbA1c 8.3(±2.8), BMI 32.6(±5.9), average METs 1.2(0.2). Significant differences were reported in mean(SD) steps/day (5,859(±2,381) in DNIL; 5,007(±3,349) in DPN and 3,271(±2,417) in DFU's and daily energy expenditure (10,868(±1,307)kJ in DNIL; 11,060(±1,916)kJ in DPN and 13,006(± 3,559) in DFU's(p <0.05). No significant differences were reported for average METs, physical activity duration or energy expenditure, sleep time or Epworth score (p>0.1). Conclusions Preliminary findings suggest people with diabetes are sedentary. Results indicate that patients with a diabetic foot ulcer work significantly less than those with neuropathy or nil complications and use significantly more energy to do so. Sleep Parameters showed no differences. Recruitment is still on going.

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With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

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