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 Acupuncture Improves Certain Aspects of Sleep in Hematopoietic Stem Cell Transplantation Patients: a Randomized Controlled Trial

2021 ◽  
Author(s):  
Sarah El Iskandarani ◽  
Lingyun Sun ◽  
Susan Qing Li ◽  
Gloria Pereira ◽  
Sergio Giralt ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Stem Cell ◽  
Hematopoietic Stem Cell Transplantation ◽  
Sleep Quality ◽  
Controlled Trial ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Hematopoietic Stem

Abstract Background High-dose chemotherapy followed by hematopoietic stem cell transplantation (HSCT) is associated with a high symptom burden including decrease in sleep quality. We conducted a randomized sham-controlled trial (#NCT01811862) to study the effect of acupuncture on sleep quality during HSCT. Methods Adult multiple myeloma patients undergoing inpatient and outpatient autologous HSCT were randomized to receive either true or sham acupuncture once daily for 5 days starting the day after chemotherapy. Sleep onset, total sleep time, sleep efficiency percentage, and sleep-onset latency time were assessed using an Actigraphy Sleep Monitor. A multi-variate regression analysis was conducted to compare the average area-under-the-curve of five acupuncture intervention days for each sleep outcome between groups, adjusted by baseline score and inpatient or outpatient chemotherapy stratum. Results Over 32 months, 63 patients were enrolled. Participants undergoing true acupuncture experienced a significant improvement in sleep efficiency when compared to sham (-6.70, 95% CI -13.15, -0.25, p=0.042). Subgroup analysis showed that the improvement is more prominent in the inpatient setting (-9.62, 95% CI -18.76, -0.47, p=0.040). True acupuncture produced noticeable yet non-significant improvement in sleep-onset latency times. Between-group differences in other sleep related variables were not statistically significant. Conclusion Our data suggest that true acupuncture may improve certain aspects of sleep, including sleep efficiency and possibly sleep-onset latency, in multiple myeloma patients undergoing HSCT. By studying patient reported outcomes in future larger scale studies, acupuncture’s role in improving sleep quality during HSCT treatment can be further elucidated.

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.

Actigraphy assessment of sleep quality among patients with acute myeloid leukaemia during induction chemotherapy

2018 ◽  
Vol 8 (3) ◽  
pp. 274-277 ◽  
Author(s):  
Chi-Fu Jeffrey Yang ◽  
Kelli Aibel ◽  
Ryan Meyerhoff ◽  
Frances Wang ◽  
David Harpole ◽  
...  
Keyword(s):  
Acute Myeloid Leukaemia ◽  
Sleep Quality ◽  
Myeloid Leukaemia ◽  
Induction Chemotherapy ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Acute Myeloid

ObjectivesPatients receiving induction chemotherapy for acute myeloid leukaemia (AML) anecdotally describe poor sleep, but sleep disturbances have not been well-characterised in this population. We aimed to test the feasibility of measuring sleep quality in AML inpatients using a wearable actigraphy device.MethodsUsing the Actigraph GT3X ‘watch’, we assessed the total sleep time, sleep onset latency, wake after sleep onset, number of awakenings after sleep onset and sleep efficiency for inpatients with AML receiving induction chemotherapy. We assessed patient self-reported sleep quality using the Pittsburgh Sleep Quality Index (PSQI).ResultsOf the 12 patients enrolled, 11 completed all actigraphy and PSQI assessments, demonstrating feasibility. Patients wore the Actigraph device for a mean (SD) of 15.92 (8.3) days, and actigraphy measures suggested poor sleep. Patients had a median average awakening length of 6.92 min, a median number of awakenings after sleep onset of 4 and a median sleep onset latency of 10.8 min. Actual median sleep efficiency (0.91) was high, suggesting that patients’ poor sleep was not due to insomnia but perhaps due to interruptions, such as administration of medications, lab draws and vital sign measurements.ConclusionsCollection of sleep quality data among inpatients with AML via a wearable actigraphy device is feasible. AML inpatients appear to have poor sleep quality and quantity, suggesting that sleep issues represent an area of unmet supportive care needs in AML. Further research in this areas is needed to inform the development of interventions to improve sleep duration and quality in hospitalised patients with AML.

Abstract 037: History Of Weight Cycling Is Prospectively Associated With Shorter And Poorer Quality Sleep, And Higher Sleep Apnea Risk In Diverse Us Women: Results From The AHA Go Red For Women Strategically Focused Research Network

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Vivian Cao ◽  
Nour Makarem ◽  
Moorea Maguire ◽  
Ivan Samayoa ◽  
Huaqing Xi ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Onset ◽  
Research Network ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Weight Cycling ◽  
Onset Latency ◽  
Cross Sectional ◽  
History Of ◽  
Insomnia Severity

Introduction: Poor sleep and history of weight cycling (HWC) are associated with worse cardiovascular health, yet limited research has evaluated the association between HWC and poor sleep patterns. Hypothesis: We hypothesized that HWC would be associated with poor sleep in US women. Methods: The AHA Go Red for Women Strategically Focused Research Network cohort at Columbia University (n=506, mean age 37 ± 15.7y, 61% racial/ethnic minority) was used to evaluate cross-sectional associations of HWC and sleep characteristics at baseline, and prospective associations of HWC from baseline with sleep measures at 1-yr. HWC, defined as losing and gaining ≥ 10 lbs at least once (excluding pregnancy), and number of WC episodes were self-reported. Sleep duration, measures of sleep quality, insomnia severity, and obstructive sleep apnea (OSA) risk were assessed using the validated Pittsburgh Sleep Quality Index, Insomnia Severity Index, and Berlin questionnaire. Linear and logistic regression models, adjusted for age, race/ethnicity, education, health insurance status, pregnancy history, and menopausal status, were used to evaluate the relation of HWC with sleep. Results: Most women reported ≥1episode of weight cycling (72%). In linear models of cross-sectional and prospective data, each additional weight cycling episode was related to shorter sleep duration, poorer sleep quality, longer sleep onset latency, greater insomnia severity, more sleep disturbances and daytime dysfunction, lower sleep efficiency, and higher sleep medication use frequency. In logistic models, HWC (≥1 vs. 0 episodes) was associated with greater odds for short sleep, poor sleep quality, long sleep onset latency ≥26 min, high OSA risk, and sleep efficiency<85% ( Table ). Conclusion: HWC predicted poor sleep among women, suggesting that weight maintenance may represent an important strategy to promote sleep health. Long-term studies are needed to disentangle the complex relations between weight fluctuations and sleep across the life course.

scholarly journals Microclimate Thermal Management Using Thermoelectric Air-Cooling Duct System Operated at Five Incremental Powers and its Effect on Sleep Adaptation of the Occupants

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3695 ◽  
Author(s):  
Kashif Irshad ◽  
Salem Algarni ◽  
Mohammad Tauheed Ahmad ◽  
Sayed Ameenuddin Irfan ◽  
Khairul Habib ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Cooling System ◽  
Sleep Onset ◽  
Air Cooling ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Test Room ◽  
Environmentally Sustainable ◽  
Highly Sensitive ◽  
The Mean

In this study, the microclimate of the test room was regulated using thermoelectric air duct cooling system (TE-AD) operated at input powers-240 W, 360 W, 480 W, 600 W, 720 W, and 840 W, on subsequent nights. Fifteen (15) healthy male volunteers were recruited to sleep under these test conditions and their sleep quality was assessed by studying objective measures such as sleep onset latency (SOL), mean skin temperature and heart rate as well as subjective parameters like predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD). There was a consistent improvement on all studied parameters when the power of the system was increased from 240 W to 720 W. The mean sleep onset latency time was reduced from (M = 40.7 +/− 0.98 min) to (M = 18.33 +/− 1.18 min) when the operating power was increased from 240 W to 720 W, denoting an improvement in sleep quality. However, increasing the power further to 840 W resulted in deteriorating cooling performance of the TE-AD system leading to an increase in temperature of the test room and reduction in sleep comfort. Analysis of subjective indices of thermal comfort viz. PMV and PPD revealed that subjects are highly sensitive towards variations in microclimate achieved by changing the operating power of the TE-AD. This device was also found to be environmentally sustainable, with estimated reduction in CO2 emission calculated to be around 38% as compared to the conventional air-conditioning.

scholarly journals The Impact of Sleep Timing, Sleep Duration, and Sleep Quality on Depressive Symptoms and Suicidal Ideation amongst Japanese Freshmen: The EQUSITE Study

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Atin Supartini ◽  
Takanori Honda ◽  
Nadzirah A. Basri ◽  
Yuka Haeuchi ◽  
Sanmei Chen ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Suicidal Ideation ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Sleep Onset ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Poor Sleep Quality ◽  
The Impact

Aim. The aim of this study was to identify the impact of bedtime, wake time, sleep duration, sleep-onset latency, and sleep quality on depressive symptoms and suicidal ideation amongst Japanese freshmen.Methods. This cross-sectional data was derived from the baseline survey of the Enhancement of Q-University Students Intelligence (EQUSITE) study conducted from May to June, 2010. A total of 2,631 participants were recruited and completed the following self-reported questionnaires: the Pittsburgh Sleep Quality Index (PSQI), the Center for Epidemiologic Studies Depression Scale (CES-D), and the original Health Support Questionnaires developed by the EQUSITE study research team.Results. Of 1,992 participants eligible for analysis, 25.5% (n=507) reported depressive symptoms (CES-D total score ≥ 16), and 5.8% (n=115) reported suicidal ideation. The present study showed that late bedtime (later than 01:30), sleep-onset latency (≥30 minutes), and poor sleep quality showed a marginally significant association with depressive symptoms. Poor sleep quality was seen to predict suicidal ideation even after adjusting for depressive symptoms.Conclusion. The current study has important implications for the role of bedtime in the prevention of depressive symptoms. Improving sleep quality may prevent the development of depressive symptoms and reduce the likelihood of suicidal ideation.

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 (&gt;=88%), while they lacked sensitivity to REM and wake (&lt;=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.

105 Sleep Behaviors Are Differentially Associated with Eating Behavior Characteristics Based on Sex

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A43-A43
Author(s):  
Rocio Barragan ◽  
Faris Zuraikat ◽  
Victoria Tam ◽  
Samantha Scaccia ◽  
Justin Cochran ◽  
...  
Keyword(s):  
Eating Behavior ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Fragmentation ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Obesity Risk ◽  
Fragmentation Index ◽  
Behavior Characteristics

Abstract Introduction Poor sleep health is a key determinant of obesity risk, largely explained by overconsumption of energy. Eating behavior characteristics are predictive of energy intake and weight change and may link sleep with risk factors for obesity. However, the relationships between sleep and dimensions of eating behavior, and potential individual differences in these relations, are not well characterized. Elucidating these relations may aid in the development of targeted strategies to mitigate obesity risk. Therefore, we aimed to 1) evaluate whether associations of sleep were related with eating behavior characteristics, 2) explore if these associations differed by sex. Methods This was a cross-sectional analysis of 179 adults aged 20–73 y (68.7% women; 64.8% with BMI≥25 kg/m2; 27.4% minority). Sleep was assessed over 2 wk using wrist actigraphy; eating behavior characteristics (dietary restraint, disinhibition and hunger) were measured with the Three-Factor Eating Questionnaire. Linear regression models were used to evaluate associations of sleep with eating behavior characteristics, adjusting for confounding variables. In separate models, sex was added as an interaction term and analyses were stratified when interactions were significant (p&lt;0.10). Results Variable (sleep midpoint standard deviation &gt;60 min) vs. stable sleep timing was associated with greater tendency towards hunger (β=0.84 ± 0.39, p=0.03). When evaluated on the continuous scale, lower sleep efficiency (β=-0.13 ± 0.05; p=0.01), longer wake after sleep onset (β=0.03 ± 0.01; p=0.01) and higher sleep fragmentation index (β=0.074 ± 0.036; p=0.041) were associated with higher dietary restraint. Sex influenced associations of sleep efficiency, sleep onset latency, and sleep fragmentation index with hunger. In men, but not women, lower sleep efficiency (β=-0.15 ± 0.05; p&lt;0.01), longer sleep onset latency (β=0.17 ± 0.07; p=0.02) and higher sleep fragmentation index (β=0.11 ± 0.04; p&lt;0.01) were associated with greater hunger. Conclusion Objective measures of sleep were associated with eating behaviors previously linked with obesity and its risk factors. Moreover, we provide evidence of sex-specific associations between poor sleep and tendency towards hunger. Our results suggest that, particularly in men, differences in eating behavior traits may underlie susceptibility to overeating in response to poor sleep. Support (if any) Supported by NIH grants R01HL128226 and R01HL142648 and AHA grant 16SFRN27950012 (PI: St-Onge).

scholarly journals Home-Based Sleep Sensor Measurements in an Older Australian Population: Before and during a Pandemic

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 5993
Author(s):  
Mahnoosh Kholghi ◽  
Claire M. Ellender ◽  
Qing Zhang ◽  
Yang Gao ◽  
Liesel Higgins ◽  
...  
Keyword(s):  
Older Adults ◽  
Time Course ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Community Dwelling ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Short Sleep Duration

Older adults are susceptible to poor night-time sleep, characterized by short sleep duration and high sleep disruptions (i.e., more frequent and longer awakenings). This study aimed to longitudinally and objectively assess the changes in sleep patterns of older Australians during the 2020 pandemic lockdown. A non-invasive mattress-based device, known as the EMFIT QS, was used to continuously monitor sleep in 31 older adults with an average age of 84 years old before (November 2019–February 2020) and during (March–May 2020) the COVID-19, a disease caused by a form of coronavirus, lockdown. Total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, time to bed, and time out of bed were measured across these two periods. Overall, there was no significant change in total sleep time; however, women had a significant increase in total sleep time (36 min), with a more than 30-min earlier bedtime. There was also no increase in wake after sleep onset and sleep onset latency. Sleep efficiency remained stable across the pandemic time course between 84–85%. While this sample size is small, these data provide reassurance that objective sleep measurement did not deteriorate through the pandemic in older community-dwelling Australians.

Sign in / Sign up

Export Citation Format

Share Document