scholarly journals A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep

Biosensors ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 185
Author(s):  
Dean J. Miller ◽  
Gregory D. Roach ◽  
Michele Lastella ◽  
Aaron T. Scanlan ◽  
Clint R. Bellenger ◽  
...  
Keyword(s):  
Eye Movement ◽  
Sensitivity And Specificity ◽  
Validation Study ◽  
Slow Wave Sleep ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Rapid Eye Movement Sleep ◽  
Two Stage ◽  
Manual Adjustment ◽  
Light Sleep

The aims of this study were to: (1) compare actigraphy (ACTICAL) and a commercially available sleep wearable (i.e., WHOOP) under two functionalities (i.e., sleep auto-detection (WHOOP-AUTO) and manual adjustment of sleep (WHOOP-MANUAL)) for two-stage categorisation of sleep (sleep or wake) against polysomnography, and; (2) compare WHOOP-AUTO and WHOOP-MANUAL for four-stage categorisation of sleep (wake, light sleep, slow wave sleep (SWS), or rapid eye movement sleep (REM)) against polysomnography. Six healthy adults (male: n = 3; female: n = 3; age: 23.0 ± 2.2 yr) participated in the nine-night protocol. Fifty-four sleeps assessed by ACTICAL, WHOOP-AUTO and WHOOP-MANUAL were compared to polysomnography using difference testing, Bland–Altman comparisons, and 30-s epoch-by-epoch comparisons. Compared to polysomnography, ACTICAL overestimated total sleep time (37.6 min) and underestimated wake (−37.6 min); WHOOP-AUTO underestimated SWS (−15.5 min); and WHOOP-MANUAL underestimated wake (−16.7 min). For ACTICAL, sensitivity for sleep, specificity for wake and overall agreement were 98%, 60% and 89%, respectively. For WHOOP-AUTO, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 90%, 60%, 86% and 63%, respectively. For WHOOP-MANUAL, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 97%, 45%, 90% and 62%, respectively. WHOOP-AUTO and WHOOP-MANUAL have a similar sensitivity and specificity to actigraphy for two-stage categorisation of sleep and can be used as a practical alternative to polysomnography for two-stage categorisation of sleep and four-stage categorisation of sleep.

Disorders of sleep

2018 ◽  
Author(s):  
Sophie West
Keyword(s):  
Chronic Disease ◽  
Eye Movement ◽  
Rem Sleep ◽  
Excessive Daytime Sleepiness ◽  
Slow Wave Sleep ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Sleep Stages ◽  
Normal Sleep ◽  
Sedative Drugs

Typically, disorders of sleep cause disturbance either to the sufferer or to their bed partner. If total sleep time is reduced, this may lead to problems with excessive daytime sleepiness, which can affect work, driving, concentration, and relationships. ‘Sleepiness’ implies an intrusive desire to fall asleep, caused by some form of sleep deprivation or sedative drugs; this is different from ‘tiredness’, which implies general fatigue, lethargy, and exhaustion and is caused by a range of conditions, including depression, chronic disease, or a busy lifestyle. Adults sleep on average for 8 hours a night. Normal sleep consists of periods of deep or slow-wave sleep, interspersed with shorter periods of dreaming or rapid-eye-movement (REM) sleep. Periods of REM sleep lengthen towards the morning and hence some people remember their dreams on waking. Different disorders of sleep can affect any of these sleep stages.

scholarly journals Sleep Organisation in Depression and Schizophrenia: Index of Endogenous Periodicity of Sleep as a State Marker [Retracted]

2013 ◽  
Vol 1 (1) ◽  
pp. 70-75
Author(s):  
Andrej Ilankovic ◽  
Aleksandar Damjanovic ◽  
Vera Ilankovic ◽  
Srdjan Milovanovic ◽  
Dusan Petrovic ◽  
...  
Keyword(s):  
Major Depression ◽  
Eye Movement ◽  
Sleep Latency ◽  
Total Sleep Time ◽  
Psychiatric Patients ◽  
Sleep Onset ◽  
Sleep Time ◽  
Rapid Eye Movement Sleep ◽  
Control Subjects ◽  
Healthy Control

Background: Sleep disorders are frequent symptoms described in psychiatric patients with major depression or schizophrenia. These patients also exhibit changes in the sleep architecture measured by polysomnography (PSG) during sleep. The aim of the present study was to identify potential biomarkers that would facilitate the diagnosis based on polysomnography (PSG) measurements.Subjects and Methods: 30 patients with schizophrenia, 30 patients with major depression and 30 healthy control subjects were investigated in the present study. The mean age in the group with schizophrenia was 36.73 (SD 6.43), in the group of patients with depression 40.77 (SD 7.66), in the healthy controls group 34.40 (SD 5.70). The gender distribution was as follows: 18 male, 12 female in the group with schizophrenia; in the group of patients with depression 11 male, 19 female; in the control group 16 male and 14 female. All subjects underwent polysomnography (PSG) for a minimum time of 8 hours according to the criteria of Rechtschaffen & Kales (1968). The following polysomnographic (PSG) parameters were analyzed: sleep latency (SL), total sleep time (TST), waking time after sleep onset (WTASO), number of awakenings (NAW), slow wave sleep (SWS), rapid eye movement sleep (REM), rapid eye movement sleep latency (REML), first REM period (REM 1), and first NREM period (NREM 1). We tested the potential of multiple sleep variables to predict diagnosis in different groups by using linear discriminate analysis (LDA).Results: There were significant differences in polysomnography (PSG) variables between healthy control subjects and psychiatric patients (total sleep time, sleep latency, number of awakenings, time of awakening after sleep onset, REM 1 latency, REM 1 and index of endogenous periodicity). Importantly, LDA was able to predict the correct diagnosis in 88% of all cases.Conclusions: The presented analysis showed commonalities and differences in polysomnography (PSG) changes in patients with major depressive disorder and in patients with schizophrenia. Our results underline the potential of polysomnography (PSG) measurements to facilitate diagnostic processes.

scholarly journals Anesthesiology Resident Night Float Duty Alters Sleep Patterns

2019 ◽  
Vol 131 (2) ◽  
pp. 401-409 ◽  
Author(s):  
Lauren K. Dunn ◽  
Amanda M. Kleiman ◽  
Katherine T. Forkin ◽  
Allison J. Bechtel ◽  
Stephen R. Collins ◽  
...  
Keyword(s):  
Eye Movement ◽  
Total Sleep Time ◽  
Night Shift ◽  
Sleep Onset ◽  
Sleep Time ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Consecutive Night ◽  
Sleep Patterns ◽  
Night Float

AbstractEditor’s PerspectiveWhat We Already Know about This TopicWhat This Article Tells Us That Is NewBackgroundResidency programs utilize night float systems to adhere to duty hour restrictions; however, the influence of night float on resident sleep has not been described. The study aim was to determine the influence of night float on resident sleep patterns and quality of sleep. We hypothesized that total sleep time decreases during night float, increases as residents acclimate to night shift work, and returns to baseline during recovery.MethodsThis was a single-center observational study of 30 anesthesia residents scheduled to complete six consecutive night float shifts. Electroencephalography sleep patterns were recorded during baseline (three nights), night float (six nights), and recovery (three nights) using the ZMachine Insight monitor (General Sleep Corporation, USA). Total sleep time; light, deep, and rapid eye movement sleep; sleep efficiency; latency to persistent sleep; and wake after sleep onset were observed.ResultsMean total sleep time ± SD was 5.9 ± 1.9 h (3.0 ± 1.2.1 h light; 1.4 ± 0.6 h deep; 1.6 ± 0.7 h rapid eye movement) at baseline. During night float, mean total sleep time was 4.5 ± 1.8 h (1.4-h decrease, 95% CI: 0.9 to 1.9, Cohen’s d = –1.1, P < 0.001) with decreases in light (2.2 ± 1.1 h, 0.7-h decrease, 95% CI: 0.4 to 1.1, d = –1.0, P < 0.001), deep (1.1 ± 0.7 h, 0.3-h decrease, 95% CI: 0.1 to 0.4, d = –0.5, P = 0.005), and rapid eye movement sleep (1.2 ± 0.6 h, 0.4-h decrease, 95% CI: 0.3 to 0.6, d = –0.9, P < 0.001). Mean total sleep time during recovery was 5.4 ± 2.2 h, which did not differ significantly from baseline; however, deep (1.0 ± 0.6 h, 0.4-h decrease, 95% CI: 0.2 to 0.6, d = –0.6, P = 0.001 *, P = 0.001) and rapid eye movement sleep (1.2 ± 0.8 h, 0.4-h decrease, 95% CI: 0.2 to 0.6, d = –0.9, P < 0.001 P < 0.001) were significantly decreased.ConclusionsElectroencephalography monitoring demonstrates that sleep quantity is decreased during six consecutive night float shifts. A 3-day period of recovery is insufficient for restorative sleep (rapid eye movement and deep sleep) levels to return to baseline.

PERCEPTION OF TOTAL SLEEP TIME (TST) IN SUBJECTS WITH VARIOUS SLEEP DISORDERS BUT NORMAL RAPID EYE MOVEMENT SLEEP (REM)

CHEST Journal ◽  
2009 ◽  
Vol 136 (4) ◽  
pp. 67S
Author(s):  
Zinobia Khan ◽  
Moses Bachan ◽  
Sara Hyatt ◽  
Joseph Ghassibi ◽  
Stephen Lund ◽  
...  
Keyword(s):  
Sleep Disorders ◽  
Eye Movement ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep

scholarly journals Slow Wave Sleep of Elite and Nonelite Gymnasts Is Influenced by Weekly Training Hours, Not by Fitness Level

2021 ◽  
pp. 1-7
Author(s):  
Jasmien Dumortier ◽  
An Mariman ◽  
Jan Boone ◽  
Liesbeth Delesie ◽  
Els Tobback ◽  
...  
Keyword(s):  
Physical Fitness ◽  
Eye Movement ◽  
Slow Wave ◽  
Slow Wave Sleep ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Fitness Level ◽  
Time In Bed ◽  
Weekly Training

Purpose: This study aimed to determine the influencing factors of potential differences in sleep architecture between elite (EG) and nonelite (NEG) female artistic gymnasts. Methods: Twelve EG (15.1 [1.5] y old) and 10 NEG (15.3 [1.8] y old) underwent a nocturnal polysomnography after a regular training day (5.8 [0.8] h vs 2.6 [0.7] h), and, on a separate test day, they performed an incremental treadmill test after a rest day in order to determine physical fitness status. A multiple linear regression assessed the predictive value of training and fitness parameters toward the different sleep phases. Total sleep time and sleep efficiency (proportion of time effectively asleep to time in bed), as well as percentage of nonrapid eye movement sleep phase 1 (NREM1) and 2 (NREM2), slow wave sleep (SWS), and rapid eye movement sleep (REM), during a single night were compared between EG and NEG using an independent-samples t test. Results: Peak oxygen uptake influenced NREM1 (β = 1.035, P = .033), while amount of weekly training hours predicted SWS (β = 1.897, P = .032). No differences were documented between EG and NEG in total sleep time and sleep efficiency. SWS was higher in EG (36.9% [11.4%]) compared with NEG (25.9% [8.3%], P = .020), compensated by a lower proportion of NREM2 (38.7% [10.2%] vs 48.4% [6.5%], P = .017), without differences in NREM1 and REM. Conclusions: The proportion of SWS was only predicted by weekly training hours and not by training hours the day of the polysomnography or physical fitness, while NREM1 was linked with fitness level. Sleep efficiency did not differ between EG and NEG, but in EG, more SWS and less NREM2 were identified.

Influence of hypothalamic and ambient temperatures on sleep in kangaroo rats

1979 ◽  
Vol 237 (1) ◽  
pp. R80-R88 ◽  
Author(s):  
S. Sakaguchi ◽  
S. F. Glotzbach ◽  
H. C. Heller
Keyword(s):  
Slow Wave Sleep ◽  
Total Sleep Time ◽  
Paradoxical Sleep ◽  
Sleep Time ◽  
Peripheral Stimulus ◽  
Kangaroo Rats ◽  
Hypothalamic Temperature ◽  
Ambient Temperatures ◽  
Thermoregulatory System

Unanesthetized, unrestrained kangaroo rats (Dipodomys) were studied to examine the changes in the frequency and duration of sleep states caused by long-term manipulations of hypothalamic temperature (Thy) at a thermoneutral (30 degrees C) and a low (20 degrees C) ambient temperature (Ta). A cold stimulus present in either the hypothalamus or the skin decreased both the total sleep time (TST) and the ratio of paradoxical sleep (PS) to TST. At a low Ta, TST, but not the PS-to-TST ratio, was increased by raising Thy, indicating that a cold peripheral stimulus could differentially inhibit PS. At a thermoneutral Ta, cooling Thy decreased both TST and the PS/TST. Changes in the amount of PS were due largely to changes in the frequency, but not the duration, of individual episodes of PS, suggesting that the transition to PS is partially dependent on the thermoregulatory conditions existing during slow-wave sleep (SWS). These results are consistent with the recent findings that the thermoregulatory system is functional during SWS but is inhibited or inactivated during PS.

Sleep apnea and effect of chemostimulation on breathing instability in mice

2003 ◽  
Vol 94 (2) ◽  
pp. 525-532 ◽  
Author(s):  
Akira Nakamura ◽  
Yasuichiro Fukuda ◽  
Tomoyuki Kuwaki
Keyword(s):  
Sleep Apnea ◽  
Eye Movement ◽  
Experimental Model ◽  
Molecular Basis ◽  
Slow Wave Sleep ◽  
Rapid Eye Movement Sleep ◽  
Body Plethysmography ◽  
Male Adult ◽  
Experimental Animals ◽  
Adult Mice

Sleep apnea occurs in humans and experimental animals. We examined whether it also arises in adult mice. Ventilation in male adult 129/Sv mice was recorded concomitantly by electroencephalograms and electromyograms for 6 h by use of body plethysmography. Apnea was defined as cessation of plethysmographic signals for longer than two respiratory cycles. While mice breathed room air, 32.3 ± 6.9 (mean ± SE, n = 5) apneas were observed during sleep but not in quiet awake periods. Sleep apneas were further classified into two types. Postsigh apneas occurred exclusively during slow-wave sleep (SWS), whereas spontaneous apneas arose during both SWS and rapid eye movement sleep. Compared with room air (9.1 ± 1.4/h of SWS), postsigh apneas were more frequent in hypoxia (13.7 ± 2.1) and less frequent in hyperoxia (3.6 ± 1.7) and hypercapnia (2.8 ± 2.1). Our data indicated that significant sleep apnea occurs in normal adult mice and suggested that the mouse could be a promising experimental model with which to study the genetic and molecular basis of respiratory regulation during sleep.

Effects of sleep-promoting factor from human urine on sleep cycle of cats

1981 ◽  
Vol 241 (4) ◽  
pp. E269-E274
Author(s):  
J. E. Garcia-Arraras
Keyword(s):  
Cerebrospinal Fluid ◽  
Eye Movement ◽  
Slow Wave ◽  
Human Urine ◽  
Slow Wave Sleep ◽  
Sleep Cycle ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Artificial Cerebrospinal Fluid ◽  
Normal Sleep

Slow-wave sleep (SWS) and rapid-eye-movement sleep (REM) were recorded in cats for 32 h a) under control conditions, b) following intraventricular infusions of artificial cerebrospinal fluid (CSF), and c) following infusions of sleep-promoting factor S prepared from human urine (SPU). During the first 12 h after receiving artificial CSF, the cats slept 4.9 +/- 0.2 h in slow-wave sleep (SWS) and 1.4 +/- 0.1 h in REM. Similar values were obtained from the same cats under control conditions. After infusions of SPU, the duration of SWS in the same cats increased to an average of 6.9 +/- 0.5 h with no significant change in REM averaged over 12 h; a transient decrease of REM in the first 4 h was fully compensated in subsequent hours. The increased SWS induced by the sleep-promoting factor from human urine subsided after 12 h, and there was no compensatory increase in wakefulness during the subsequent 20 h. The normal sleep cycle was not affected. In cats, therefore, the primary effect of SPU is to increase normal SWS, with little effect on REM.

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