The Relationship between Sleep Quality and Mattress Types

2002 ◽  
Vol 46 (6) ◽  
pp. 745-749 ◽  
Author(s):  
Se Jin Park ◽  
Hyun Ja Lee
Keyword(s):  
Sleep Quality ◽  
Skin Temperature ◽  
Sleep Stage ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Subjective Rating ◽  
Deep Sleep ◽  
Mean Skin Temperature ◽  
Subjective Ratings ◽  
The Relationship

Information of sleep stage was one of the most important clues for sleep quality. The purpose of this study was to measure the effects of mattress types on sleep quality, the skin temperature and to estimate the subjective rating. The hypothesis was tested whether sleep quality was different when subjects slept on mattress suitable for the bodily shape or not. Polysomnography is basically the recording of sleep. The several channels of brain waves (EEG), eyes (EOG), chin movements (EMG) and heart (ECG) were monitored. Six subjects spent 6 days and nights in the laboratory and the data of sleeping 7h for each of 3 nights was analyzed. Mean skin temperature, deep sleep (III and IV), sleep efficiency, sleep latency and subjective ratings were significantly affected with mattress types. When subjects slept in comfortable beds, mean skin temperature was higher than that of uncomfortable bed. Their skin temperature of the lower body, sleep efficiency and the percentage of deep sleep were higher, too. The percentage of wake after sleep onset was lower when subject slept in a comfortable bed.

Utility of Activity Monitors and Thermometry in Assessing Sleep Stages and Sleep Quality

2018 ◽  
Vol 1 (3) ◽  
pp. 108-121
Author(s):  
Natashia Swalve ◽  
Brianna Harfmann ◽  
John Mitrzyk ◽  
Alexander H. K. Montoye
Keyword(s):  
Sleep Quality ◽  
Skin Temperature ◽  
Sleep Stage ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Stages ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Activity Monitors ◽  
Research Grade

Activity monitors provide an inexpensive and convenient way to measure sleep, yet relatively few studies have been conducted to validate the use of these devices in examining measures of sleep quality or sleep stages and if other measures, such as thermometry, could inform their accuracy. The purpose of this study was to compare one research-grade and four consumer-grade activity monitors on measures of sleep quality (sleep efficiency, sleep onset latency, and wake after sleep onset) and sleep stages (awake, sleep, light, deep, REM) against an electroencephalography criterion. The use of a skin temperature device was also explored to ascertain whether skin temperature monitoring may provide additional data to increase the accuracy of sleep determination. Twenty adults stayed overnight in a sleep laboratory during which sleep was assessed using electroencephalography and compared to data concurrently collected by five activity monitors (research-grade: ActiGraph GT9X Link; consumer-grade: Fitbit Charge HR, Fitbit Flex, Jawbone UP4, Misfit Flash) and a skin temperature sensor (iButton). The majority of the consumer-grade devices overestimated total sleep time and sleep efficiency while underestimating sleep onset latency, wake after sleep onset, and number of awakenings during the night, with similar results being seen in the research-grade device. The Jawbone UP4 performed better than both the consumer- and research-grade devices, having high levels of agreement overall and in epoch-by-epoch sleep stage data. Changes in temperature were moderately correlated with sleep stages, suggesting that addition of skin temperature could increase the validity of activity monitors in sleep measurement.

scholarly journals Physical Activity and Inhibitory Control: The Mediating Role of Sleep Quality and Sleep Efficiency

2021 ◽  
Vol 11 (5) ◽  
pp. 664
Author(s):  
Lin Li ◽  
Qian Yu ◽  
Wenrui Zhao ◽  
Fabian Herold ◽  
Boris Cheval ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sleep Quality ◽  
Inhibitory Control ◽  
Sleep Efficiency ◽  
Equation Modeling ◽  
Control Performance ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
Sleep Parameters ◽  
The Relationship

Objectives: the current study aimed to investigate the relationship between physical activity (PA) level and inhibitory control performance and then to determine whether this association was mediated by multiple sleep parameters (i.e., subjective sleep quality, sleep duration, sleep efficiency, and sleep disturbance). Methods: 180 healthy university students (age: 20.15 ± 1.92 years) from the East China Normal University were recruited for the present study. PA level, sleep parameters, and inhibitory control performance were assessed using the International Physical Activity Questionnaire (IPAQ), the Pittsburgh Sleep Quality Index Scale (PSQI), and a Stroop test, respectively. The data were analyzed using structural equation modeling. Results: A higher level of PA was linked to better cognitive performance. Furthermore, higher subjective sleep quality and sleep efficiency were associated with better inhibitory control performance. The mediation analysis revealed that subjective sleep quality and sleep efficiency mediated the relationship between PA level and inhibitory control performance. Conclusion: our results are in accordance with the literature and buttress the idea that a healthy lifestyle that involves a relatively high level of regular PA and adequate sleep patterns is beneficial for cognition (e.g., inhibitory control performance). Furthermore, our study adds to the literature that sleep quality and sleep efficiency mediates the relationship between PA and inhibitory control performance, expanding our knowledge in the field of exercise cognition.

Sleep and the gut microbiota in preschool aged children

SLEEP ◽  
2022 ◽  
Author(s):  
Yanan Wang ◽  
Marcel van de Wouw ◽  
Lauren Drogos ◽  
Elnaz Vaghef-Mehrabani ◽  
Raylene A Reimer ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Wake Time ◽  
Novel Association ◽  
Human Adults ◽  
Time Awake ◽  
Nighttime Sleep ◽  
The Relationship ◽  
Preschool Aged Children

Abstract Sleep plays a significant role in the mental and physical development of children. Emerging evidence in animals and human adults indicates a relationship between sleep and the gut microbiota; however, it is unclear whether the sleep of preschoolers during a key developmental period, associates with features of their gut microbiota. The objective of this study was to assess the relationship between sleep and gut microbiota in preschool aged children (4.37 ±0.48 years, n=143). Sleep measures included total nighttime sleep (TST), sleep efficiency (SE), and wake-time after sleep onset (WASO) assessed using actigraphy. Beta-diversity differences between children with low and high TST (p =0.048) suggest gut microbiota community differences. Particularly, relative abundance of Bifidobacterium was higher in the high TST group and Bacteroides, was higher in children who had higher SE and low WASO (LDA score >2). In contrast, some Lachnospiraceae members including Blautia and Coprococcus 1 were associated with shorter nighttime sleep duration and less efficiency, respectively. We also found a group of faecal metabolites, including specific neuroactive compounds and immunomodulating metabolites were associated with greater sleep efficiency and less time awake at night. Notably, tryptophan and its metabolizing products were higher in children who had higher SE or lower WASO (LDA score >2); concentration of propionate was higher in children with lower WASO (p =0.036). Overall, our results reveal a novel association between sleep and gut microbiota in preschool aged children. Longer nighttime sleep and greater sleep efficiency were associated with specific commensal bacteria that may regulate sleep through modulating neurotransmitter metabolism and the immune system.

The sleep macroarchitecture of children at risk for depression recruited in sleep centers

2012 ◽  
Vol 28 (3) ◽  
pp. 168-173 ◽  
Author(s):  
F. Bat-Pitault ◽  
D. Da Fonseca ◽  
S. Cortese ◽  
Y. Le Strat ◽  
L. Kocher ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
High Risk ◽  
Children And Adolescents ◽  
Depressive Episode ◽  
Risk Group ◽  
Sleep Stage ◽  
Sleep Onset ◽  
High Risk Group ◽  
Sleep Efficiency ◽  
History Of

AbstractObjectiveThe primary aim of this study was to compare the sleep macroarchitecture of children and adolescents whose mothers have a history of depression with children and adolescents whose mothers do not.MethodPolysomnography (PSG) and Holter electroencephalogram (EEG) were used to compare the sleep architecture of 35 children whose mothers had at least one previous depressive episode (19 boys, aged 4–18 years, “high-risk” group) and 25 controls (13 males, aged 4–18 years, “low-risk” group) whose mothers had never had a depressive episode. The total sleep time, wakefulness after sleep onset (WASO), sleep latency, sleep efficiency, number of awakenings per hour of sleep, percentages of time spent in each sleep stage, rapid eye movement (REM) latency and the depressive symptoms of participants were measured.ResultsIn children (4–12 years old), the high-risk group exhibited significantly more depressive symptoms than controls (P = 0.02). However, PSG parameters were not significantly different between high-risk children and controls. In adolescents (13–18 years old), the high-risk subjects presented with significantly more depressive symptoms (P = 0.003), a significant increase in WASO (P = 0.019) and a significant decrease in sleep efficiency compared to controls (P = 0.009).ConclusionThis study shows that children and adolescents born from mothers with a history of at least one depressive episode had significantly more depressive symptoms than controls. However, only high-risk adolescents presented with concurrent alterations of sleep macroarchitecture.

scholarly journals 1134 Light Exposure At Daytime On Sleep Quality In Stroke Patient During Rehabilitation

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A432-A432
Author(s):  
W Liao ◽  
S Lin ◽  
N Meng ◽  
H Tin ◽  
S Tsai ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Stroke Patient ◽  
Light Exposure ◽  
Sleep Onset ◽  
Bright Light ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Cross Sectional ◽  
Melatonin Concentration ◽  
Improve Sleep Quality

Abstract Introduction Lights maintain the day and night rhythm to set patients’ “wake-up cycle” and to stabilize their physiological functions, which may be expected to improve sleep. This study was aimed to investigate the relations between sleep quality and daytime light exposure in stroke patient during rehabilitation. Methods A cross-sectional study design was adopted and 120 stroke patients were recruited from rehabilitation wards of two medical centers and 116 patients completed this study. Research instruments including the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Sleep Log, and Somnowatch (Germany) for actigaphy sleep and light were used to collect data and urinary melatonin concentration were measured. Results 47.4% of the patients had poor sleep quality (PSQI>5), 74.1% had actigraphic sleep efficiency less than 85%, and 90.5% waked more than 30 minutes after sleep onset. The average exposure time at lower level light (≤149 lux) were 288.8 minutes, accounting for 48% of the day (8:00-18:00). Compared to lower light exposure group (less than 319.5 min at >150 lux), those who exposed to higher level light (more than 319.5 min at >150 lux) had increased 52.1 minutes in actigraphic total sleep time (TST, t=-2.134, p=0.035), increased 8% in actigraphic sleep efficiency (SE, t=-2.053, p=0.042), and decreased 41.1 minutes in actigraphic wake-after-sleep-onset (WASO, t=2.209, p=0.029). Urinary melatonin concentration increased 52.7 pg/ml, but not statistically significant (t=-1.277, p=0.205). Result of multiple regression analysis showed that after controlling for age, gender, post-stroke complications, and environmental interference, time of bright light exposure significantly affected subjective sleep satisfaction (p=0.014), TST (p=0.04), SE (p=0.041), and WASO (p=0.026). Conclusion Increasing time of bright illumination (≥150 lux) during daytime may improve sleep quality. Results of this study provide empirical references for non-drug intervention to improve sleep quality in patients with stroke. Support This study was supported by the Ministry of Science and Technology, MOST 105-2628-B-040 -005 -MY2.

Cancer-related insomnia: Evaluation by mobile technology.

2015 ◽  
Vol 33 (29_suppl) ◽  
pp. 107-107
Author(s):  
Brenda O'Connor ◽  
Pauline Ui Dhuibhir ◽  
Declan Walsh
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Median Duration ◽  
Metastatic Cancer ◽  
Eastern Cooperative Oncology Group ◽  
Sleep Onset ◽  
Severity Index ◽  
Sleep Efficiency ◽  
Subjective Sleep Quality ◽  
Time In Bed

107 Background: Insomnia is difficulty with sleep onset, maintenance, early morning wakening or non-restorative sleep. Cancer prevalence is 30-75%. Daytime consequences include fatigue. It is under-reported and impairs quality of life. Measurement previously required sleep laboratories. Technology advances help real-time measurement in the natural environment. This study investigated the feasibility and acceptability of a wireless device to evaluate sleep in cancer. Methods: Prospective observational study: Stage A: 10 consecutive in-patient hospice admissions; Stage B: 20 consecutive community patients Sleep quality was rated by Insomnia Severity Index (ISI). Participants used a wireless non-contact bedside monitor (SleepMinder) for 3 nights. Acceptability questionnaires were completed by participant and nurse (Stage A) or family (Stage B).Descriptive statistics were generated by Microsoft Excel. Results: 30 participants with metastatic cancer were recruited. Median age: 63 years (47-84). Median Eastern Cooperative Oncology Group (ECOG) performance score: 2 (0-3). In-patient (n=10): In 50%, sleep onset was delayed >30 minutes. Median duration: 8 hours. Median awakenings per night: 1 (0-8). Median sleep efficiency (proportion of time in bed spent asleep): 89% (74-100%). ISI score correlated with sleep duration in 70%. Participants and nurses reported 100% device acceptability. Community (n=20): Sleep onset was delayed >30 minutes in 25%. Median duration: 8 hours. Median awakenings per night: 3 (0-10). Median sleep efficiency: 91% (46-100). ISI score correlated with sleep duration in 90%. Participants and family reported 100% device acceptability. Conclusions: (1)A wireless monitor effectively measures sleep in cancer in both inpatient and community settings, (2) High acceptability supports clinical use, (3) Subjective sleep quality reports correlate with device, and (4) Further research: evaluate sleep improvement interventions with device.

372 Sleep Hygiene Compliance and Sleep in Young Adult Drinkers with Insomnia: A Daily Analysis

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A148-A148
Author(s):  
Mary Beth Miller ◽  
Ashley Curtis ◽  
Nicole Hall ◽  
Adam Everson ◽  
Chan Jeong Park ◽  
...  
Keyword(s):  
Young Adult ◽  
Sleep Quality ◽  
Stimulus Control ◽  
Sleep Onset ◽  
Heavy Drinking ◽  
Empirical Support ◽  
Sleep Hygiene ◽  
Sleep Efficiency ◽  
Vigorous Exercise ◽  
Wrist Actigraphy

Abstract Introduction Empirical evidence linking sleep hygiene practices to subsequent sleep parameters – and the extent to which those compare to evidence-based practices such as stimulus control – is limited. This study examined the daily impact of recommendation compliance on sleep in a sample of young adult drinkers with insomnia. Methods Young adults (18-30y; N=56, 75% female) who met diagnostic criteria for insomnia and reported past-month binge drinking wore wrist actigraphy and completed online sleep diaries for 7+ days (492 reports). Diaries assessed compliance with nine sleep hygiene recommendations: to limit naps; limit caffeine; avoid caffeine after 12p; avoid tobacco, alcohol, vigorous exercise, and heavy meals within 2 hours of bedtime; avoid bright light within 30 minutes of bedtime; and utilize a bedtime routine. If participants reported wake after sleep onset, diaries also assessed if they had gotten out of bed and returned to bed only when sleepy (partial stimulus control instructions). Multilevel models examined three outcomes: sleep quality, self-reported sleep efficiency, and actigraphy-measured sleep efficiency (α=.05/3≤.017). Covariates included gender; college enrollment; weekday versus weekend; and between-person differences in insomnia severity, hazardous drinking, and average compliance, Results Participants self-reported better sleep efficiency on days that they avoided naps (B=3.64, p=.004; 95% CI=1.20, 6.08). They also self-reported better sleep quality (B=0.40, p<.001; 95% CI=0.19, 0.60) and sleep efficiency (B=3.94, p<.001; 95% CI=1.76; 6.12) on days that they followed stimulus control. Surprisingly, they reported worse sleep quality (B=-0.28, p=.017; 95% CI=-0.51, -0.05) and sleep efficiency (B=-3.74, p=.002; 95% CI=-6.08, -1.40) on days that they avoided alcohol use before bedtime. No variables were significantly associated with actigraphy-based sleep efficiency. At the between-person level, participants reporting more at-risk drinking reported worse sleep quality (B=-0.04, p=.017; 95% CI=-0.08, -0.01). Conclusion Data provide empirical support for recommendations that young adult drinkers with insomnia avoid naps and get out of bed during nighttime awakenings. Although heavier drinkers reported worse sleep quality than lighter drinkers, they also reported better subjective (but not objective) sleep on nights they drank close to bedtime. We speculate that this is due to later bedtimes on heavy-drinking nights. Support (if any) University of Missouri Research Board (PI Miller)

scholarly journals 1205 Activity Trackers As A Tool In Sleep Research: Determining Discrepancies In Trackers Vs. PSG

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A460-A461
Author(s):  
E P Pollet ◽  
D P Pollet ◽  
B Long ◽  
A A Qutub
Keyword(s):  
Sleep Disorders ◽  
Sleep Stage ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Stages ◽  
Sleep Staging ◽  
Sleep Study ◽  
Activity Tracker ◽  
Activity Trackers ◽  
Large Populations

Abstract Introduction Fitness-based wearables and other emerging sensor technologies have the potential to track sleep across large populations longitudinally in at-home environments. To understand how these devices can inform research studies, limitations of available trackers need to be compared to traditional polysomnography (PSG). Here we assessed discrepancies in sleep staging in activity trackers vs. PSG in subjects with various sleep disorders. Methods Twelve subjects (age 41-78, 7f, 5m) wore a Fitbit Charge 3 while undergoing a scheduled sleep study. Six subjects had been previously diagnosed with a sleep disorder (5 OSA, 1 CSA). 4 subjects used CPAP throughout the night, 2 had a split night (CPAP 2nd half of the night), and 6 had a PSG only. Activity tracker staging was compared to 2 RPSGTs staging. Results Of the 12 subjects, eight subjects’ sleep was detected in the activity tracker, and compared across sleep stages to the PSG (7 female, 1 male, ages 41-78, AHI 0.3-87, RDI 0.5-94.4, sleep efficiency 74%+/-18, 4 PSG, 1 split, 3 CPAP). The activity tracker matched either tech 52% (+/- 13). The average difference in score tech and activity tracker staging for sleep onset (SO) was 16 +/- 15 minutes and wake after sleep onset was 43.5 +/- 44 minutes. Sensitivity, specificity, and balanced accuracy were found for each sleep stage. Respectively, Wake: 0.45+/-0.27, 0.97+/-0.03, 0.71+/-0.12, REM: 0.41+/-0.30, 0.90+/-0.06, 0.60+/-0.28, Light: 0.71+/-0.09, 0.58+/-0.19, 0.65+/-0.10, Deep: 0.63+/-0.52, 0.88+/-0.05, 0.59+/-0.49. Conclusion From this study of 12 subjects seen at a sleep clinic for suspected sleep disorders, activity trackers performed best in wake, REM and deep sleep specificity (>=88%), while they lacked sensitivity to REM and wake (<=45%) stages. The tracker did not detect sleep in 4 subjects who had elevated AHI or low sleep efficiency. Further analysis can identify whether discrepancies between the Fitbit and PSG can be predicted by distinct patterns in sleep staging and/or identify subject exclusion criteria for activity tracking studies. Support This project in on-going with the support of Academy Diagnostics Sleep and EEG Center and staff.

Physical exercise may improve sleep quality in children and adolescents with Fontan circulation

2019 ◽  
Vol 29 (7) ◽  
pp. 922-929 ◽  
Author(s):  
Eva R. Hedlund ◽  
Li Villard ◽  
Bo Lundell ◽  
Gunnar Sjöberg
Keyword(s):  
Physical Exercise ◽  
Sleep Quality ◽  
Training Program ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Healthy Controls ◽  
Before And After ◽  
Improve Sleep Quality ◽  
Fontan Patients

AbstractObjective:To study physical activity and sleep in Fontan patients and healthy controls before and after an endurance training program, and after 1 year.Method:Fontan patients (n = 30) and healthy controls (n = 25) wore accelerometers for seven consecutive days and nights during a school week before and after a 12-week endurance training program and after 1 year.Results:Patients had similar sleep duration and sleep efficiency as healthy controls. Latency to sleep onset in minutes was longer for patients than controls (22.4 (4.3–55.3) minutes versus 14.8 (8.6–29.4) minutes, p < 0.01). More time in moderate-to-vigorous activity daytime was correlated with increased sleep time (p < 0.05; r2 = 0.20), improved sleep efficiency (p < 0.01; r2 = 0.24) and less time as wake after sleep onset (p < 0.05; r2 = 0.21) for patients but not controls. Sleep variables did not change after the exercise intervention for patients or controls. After 1 year, patients had decreased total sleep time, decreased sleep efficiency, increased accelerometer counts during sleep and more time as wake after sleep onset during sleep time, but not controls.Conclusions:Fontan patients have prolonged latency to sleep onset compared with controls. More time in physical activities was correlated with better sleep quality for the patients. Also, subjects with low sleep efficiency and long latency to sleep onset may benefit most from physical exercise. These patients should be encouraged to engage in individually designed physical exercise as this could improve sleep quality.

scholarly journals Subjective Ratings of Beauty and Aesthetics: Correlations With Statistical Image Properties in Western Oil Paintings

i-Perception ◽  
2017 ◽  
Vol 8 (3) ◽  
pp. 204166951771547 ◽  
Author(s):  
Gregor U. Hayn-Leichsenring ◽  
Thomas Lehmann ◽  
Christoph Redies
Keyword(s):  
Subjective Evaluation ◽  
Objective Measures ◽  
Subjective Rating ◽  
Subjective Ratings ◽  
Aesthetic Value ◽  
Data Set ◽  
Oil Paintings ◽  
Artistic Value ◽  
Subjective Evaluations ◽  
The Relationship

For centuries, oil paintings have been a major segment of the visual arts. The JenAesthetics data set consists of a large number of high-quality images of oil paintings of Western provenance from different art periods. With this database, we studied the relationship between objective image measures and subjective evaluations of the images, especially evaluations on aesthetics (defined as artistic value) and beauty (defined as individual liking). The objective measures represented low-level statistical image properties that have been associated with aesthetic value in previous research. Subjective rating scores on aesthetics and beauty correlated not only with each other but also with different combinations of the objective measures. Furthermore, we found that paintings from different art periods vary with regard to the objective measures, that is, they exhibit specific patterns of statistical image properties. In addition, clusters of participants preferred different combinations of these properties. In conclusion, the results of the present study provide evidence that statistical image properties vary between art periods and subject matters and, in addition, they correlate with the subjective evaluation of paintings by the participants.

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