Performance of wearable sleep trackers during nocturnal sleep and periods of simulated real-world smartphone use

GOAL AND AIMS

To test sleep/wake transition detection of consumer sleep trackers and research-grade actigraphy during nocturnal sleep and simulated peri-sleep behavior involving minimal movement.

FOCUS TECHNOLOGY

Oura Ring Gen 3, Fitbit Sense, AXTRO Fit 3, Xiaomi Mi Band 7, and ActiGraph GT9X.

REFERENCE TECHNOLOGY

Polysomnography.

SAMPLE

Sixty-three participants (36 female) aged 20-68.

DESIGN

Participants engaged in common peri-sleep behavior (reading news articles, watching videos, and exchanging texts) on a smartphone before and after the sleep period. They were woken up during the night to complete a short questionnaire to simulate responding to an incoming message.

CORE ANALYTICS

Detection and timing accuracy for the sleep onset times and wake times.

ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES

Discrepancy analysis both including and excluding the peri-sleep activity periods. Epoch-by-epoch analysis of rate and extent of wake misclassification during peri-sleep activity periods.

CORE OUTCOMES

Oura and Fitbit were more accurate at detecting sleep/wake transitions than the actigraph and the lower-priced consumer sleep tracker devices. Detection accuracy was less reliable in participants with lower sleep efficiency.

IMPORTANT ADDITIONAL OUTCOMES

With inclusion of peri-sleep periods, specificity and Kappa improved significantly for Oura and Fitbit, but not ActiGraph. All devices misclassified motionless wake as sleep to some extent, but this was less prevalent for Oura and Fitbit.

CORE CONCLUSIONS

Performance of Oura and Fitbit is robust on nights with suboptimal bedtime routines or minor sleep disturbances. Reduced performance on nights with low sleep efficiency bolsters concerns that these devices are less accurate for fragmented or disturbed sleep.

Selecting a sleep tracker from EEG-based, iteratively improved, low-cost multisensor, and actigraphy-only devices

AIMS

Evaluate the performance of 6 wearable sleep trackers across 4 classes (EEG-based headband, research-grade actigraphy, iteratively improved consumer tracker, low-cost consumer tracker).

FOCUS TECHNOLOGY

Dreem 3 headband, Actigraph GT9X, Oura Ring Gen3, Fitbit Sense, Xiaomi Mi Band 7, Axtro Fit3.

REFERENCE TECHNOLOGY

In-lab polysomnography with 3-reader, consensus sleep scoring.

SAMPLE

Sixty participants (26 males) across 3 age groups (18-30, 31-50, and 51-70years).

DESIGN

Overnight in a sleep laboratory from habitual sleep time to wake time.

CORE ANALYTICS

Discrepancy and epoch-by-epoch analyses for sleep/wake (2-stage) and sleep-stage (4-stage; wake/light/deep/rapid eye movement) classification (devices vs. polysomnography).

CORE OUTCOMES

EEG-based Dreem performed the best (2-stage kappa=0.76, 4-stage kappa=0.76-0.86) with the lowest total sleep time, sleep efficiency, sleep onset latency, and wake after sleep onset discrepancies vs. polysomnography. This was followed by the iteratively improved consumer trackers: Oura (2-stage kappa=0.64, 4-stage kappa=0.55-0.70) and Fitbit (2-stage kappa=0.58, 4-stage kappa=0.45-0.60) which had comparable total sleep time and sleep efficiency discrepancies that outperformed accelerometry-only Actigraph (2-stage kappa=0.47). The low-cost consumer trackers had poorest overall performance (2-stage kappa<0.31, 4-stage kappa<0.33).

IMPORTANT ADDITIONAL OUTCOMES

Proportional biases were driven by nights with poorer sleep (longer sleep onset latencies and/or wake after sleep onset).

CORE CONCLUSION

EEG-based Dreem is recommended when evaluating poor quality sleep or when highest accuracy sleep-staging is required. Iteratively improved non-EEG sleep trackers (Oura, Fitbit) balance classification accuracy with well-tolerated, and economic deployment at-scale, and are recommended for studies involving mostly healthy sleepers. The low-cost trackers, can log time in bed but are not recommended for research use.

Insights into vascular physiology from sleep photoplethysmography

STUDY OBJECTIVES

Photoplethysmography (PPG) in consumer sleep trackers is now widely available and used to assess heart rate variability (HRV) for sleep staging. However, PPG waveform changes during sleep can also inform about vascular elasticity in healthy persons who constitute a majority of users. To assess its potential value, we traced the evolution of PPG pulse waveform during sleep alongside measurements of HRV and blood pressure (BP).

METHODS

Seventy-eight healthy adults (50% male, median [IQR range] age: 29.5 [23.0, 43.8]) underwent overnight polysomnography (PSG) with fingertip PPG, ambulatory blood pressure monitoring, and electrocardiography (ECG). Selected PPG features that reflect arterial stiffness: systolic to diastolic distance (∆T_norm), normalized rising slope (Rslope) and normalized reflection index (RI) were derived using a custom-built algorithm. Pulse arrival time (PAT) was calculated using ECG and PPG signals. The effect of sleep stage on these measures of arterial elasticity and how this pattern of sleep stage evolution differed with participant age were investigated.

RESULTS

BP, heart rate (HR) and PAT were reduced with deeper non-REM sleep but these changes were unaffected by the age range tested. After adjusting for lowered HR, ∆T_norm, Rslope, and RI showed significant effects of sleep stage, whereby deeper sleep was associated with lower arterial stiffness. Age was significantly correlated with the amount of sleep-related change in ∆T_norm, Rslope, and RI, and remained a significant predictor of RI after adjustment for sex, body mass index, office BP, and sleep efficiency.

CONCLUSIONS

The current findings indicate that the magnitude of sleep-related change in PPG waveform can provide useful information about vascular elasticity and age effects on this in healthy adults.

Nocturnal Blood Pressure Estimation from Sleep Plethysmography Using Machine Learning

BACKGROUND

Elevated nocturnal blood pressure (BP) is a risk factor for cardiovascular disease (CVD) and mortality. Cuffless BP assessment aided by machine learning could be a desirable alternative to traditional cuff-based methods for monitoring BP during sleep. We describe a machine-learning-based algorithm for predicting nocturnal BP using single-channel fingertip plethysmography (PPG) in healthy adults.

METHODS

Sixty-eight healthy adults with no apparent sleep or CVD (53% male), with a median (IQR) age of 29 (23-46 years), underwent overnight polysomnography (PSG) with fingertip PPG and ambulatory blood pressure monitoring (ABPM). Features based on pulse morphology were extracted from the PPG waveforms. Random forest models were used to predict night-time systolic blood pressure (SBP) and diastolic blood pressure (DBP).

RESULTS

Our model achieved the highest out-of-sample performance with a window length of 7 s across window lengths explored (60 s, 30 s, 15 s, 7 s, and 3 s). The mean absolute error (MAE ± STD) was 5.72 ± 4.51 mmHg for SBP and 4.52 ± 3.60 mmHg for DBP. Similarly, the root mean square error (RMSE ± STD) was 6.47 ± 1.88 mmHg for SBP and 4.62 ± 1.17 mmHg for DBP. The mean correlation coefficient between measured and predicted values was 0.87 for SBP and 0.86 for DBP. Based on Shapley additive explanation (SHAP) values, the most important PPG waveform feature was the stiffness index, a marker that reflects the change in arterial stiffness.

CONCLUSION

Our results highlight the potential of machine learning-based nocturnal BP prediction using single-channel fingertip PPG in healthy adults. The accuracy of the predictions demonstrated that our cuffless method was able to capture the dynamic and complex relationship between PPG waveform characteristics and BP during sleep, which may provide a scalable, convenient, economical, and non-invasive means to continuously monitor blood pressure.

Advantage conferred by overnight sleep on schema-related memory may last only a day

Study Objectives

Sleep contributes to declarative memory consolidation. Independently, schemas benefit memory. Here we investigated how sleep compared with active wake benefits schema consolidation 12 and 24 hours after initial learning.

Methods

Fifty-three adolescents (age: 15-19 years) randomly assigned into sleep and active wake groups participated in a schema-learning protocol based on transitive inference (i.e. If B > C and C > D then B > D). Participants were tested immediately after learning and following 12-, and 24-hour intervals of wake or sleep for both the adjacent (e.g. B-C, C-D; relational memory) and inference pairs: (e.g.: B-D, B-E, and C-E). Memory performance following the respective 12- and 24-hour intervals were analyzed using a mixed ANOVA with schema (schema, no-schema) as the within-participant factor, and condition (sleep, wake) as the between-participant factor.

Results

Twelve hours after learning, there were significant main effects of condition (sleep, wake) and schema, as well as a significant interaction, whereby schema-related memory was significantly better in the sleep condition compared to wake. Higher sleep spindle density was most consistently associated with greater overnight schema-related memory benefit. After 24 hours, the memory advantage of initial sleep was diminished.

Conclusions

Overnight sleep preferentially benefits schema-related memory consolidation following initial learning compared with active wake, but this advantage may be eroded after a subsequent night of sleep. This is possibly due to delayed consolidation that might occur during subsequent sleep opportunities in the wake group.

Clinical Trial Information

Name: Investigating Preferred Nap Schedules for Adolescents (NFS5) URL: https://clinicaltrials.gov/ct2/show/NCT04044885. Registration: NCT04044885.

Adherence to 24-Hour Movement Recommendations and Health Indicators in Early Adolescence: Cross-Sectional and Longitudinal Associations in the Adolescent Brain Cognitive Development Study

PURPOSE

Adherence to 24-hour movement guidelines of ≥60 minutes of physical activity, ≤2 hours of screen time, and 9-11 hours of sleep has been shown to benefit cognitive, physical, and psychosocial health in children and young adolescents aged 5-13 years. However, these findings have mostly been based on cross-sectional studies or relatively small samples and the associations between adherence to guidelines and brain structure remain to be evaluated.

METHODS

Data from the Adolescent Brain Cognitive Development℠ (ABCD) study of 10,574 early adolescents aged 9-14 years from September 2016 to January 2021 were used to examine whether adherence to 24-hour movement guidelines benefits cognition (general cognitive ability, executive function, and learning/memory assessed by the National Institutes of Health Toolbox neurocognitive battery), body mass index, psychosocial health (internalizing, externalizing, and total problems from the parent-reported Child Behavior Checklist), and magnetic resonance imaging-derived brain morphometric measures at baseline (T1), ∼2 years later (T2), and longitudinally from T1 to T2 (T2-T1). Multivariable linear mixed models were used, with adjustments for sociodemographic confounders. Time elapsed and T1 outcome measures were also controlled for in longitudinal models.

RESULTS

Better cognitive scores, fewer behavioral problems, lower adiposity levels, and greater gray matter volumes were observed in those who met both sleep and screen time recommendations compared to those who met none. Longitudinal follow-up further supports these findings; participants who met both recommendations at T1 and T2 evidenced better outcome measures than those who met none.

DISCUSSION

These findings support consideration of integrated rather than isolated movement recommendations across the day in early adolescence for better cognitive, physical and psychosocial health. Although the associations between physical activity and health indicators were less consistent in this study, the significant findings from sleep and screen time demonstrate the importance of considering movement recommendations in an integrated rather than isolated manner for adolescent health. It is recommended that movement behaviors be simultaneously targeted for better developmental outcomes.

Influence of Mid-Afternoon Nap Duration and Sleep Parameters on Memory Encoding, Mood, Processing Speed and Vigilance

STUDY OBJECTIVES

To determine how mid-afternoon naps of differing durations benefit memory encoding, vigilance, speed-of-processing (SOP), mood, and sleepiness; to evaluate if these benefits extend past 3 h post-awakening and to examine how sleep macrostructure during naps modulate these benefits.

METHODS

Following short habitual sleep, 32 young adults underwent 4 experimental conditions in randomized order: wake; naps of 10min, 30min and 60min duration verified with polysomnography. A 10-min test battery was delivered at a pre-nap baseline, and at 5min, 30min, 60min and 240min post nap. Participants encoded pictures 90min post-nap and were tested for recognition 210min later.

RESULTS

Naps ranging from 10-60mins increased positive mood and alleviated subjective sleepiness up to 240min post-nap. Compared to wake, only naps of 30min improved memory encoding. Improvements for vigilance were moderate, and benefits for SOP were not observed. Sleep inertia was observed for the 30min to 60min naps but was resolved within 30mins after waking. We found no significant associations between sleep macrostructure and memory benefits.

CONCLUSIONS

With short habitual sleep, naps ranging from 10-60mins had clear and lasting benefits for positive mood and subjective sleepiness / alertness. Cognitive improvements were moderate, with only the 30min nap showing benefits for memory encoding. While there is no clear 'winning' nap duration, a 30min nap appears to have the best trade-off between practicability and benefit.

Mindfulness-based therapy for insomnia for older adults with sleep difficulties: a randomized clinical trial

OBJECTIVE

Poor sleep is a modifiable risk factor for multiple disorders. Frontline treatments (e.g. cognitive-behavioral therapy for insomnia) have limitations, prompting a search for alternative approaches. Here, we compare manualized Mindfulness-Based Therapy for Insomnia (MBTI) with a Sleep Hygiene, Education, and Exercise Program (SHEEP) in improving subjective and objective sleep outcomes in older adults.

METHODS

We conducted a single-site, parallel-arm trial, with blinded assessments collected at baseline, post-intervention and 6-months follow-up. We randomized 127 participants aged 50-80, with a Pittsburgh Sleep Quality Index (PSQI) score ⩾5, to either MBTI (n = 65) or SHEEP (n = 62), both 2 hr weekly group sessions lasting 8 weeks. Primary outcomes included PSQI and Insomnia Severity Index, and actigraphy- and polysomnography-measured sleep onset latency (SOL) and wake after sleep onset (WASO).

RESULTS

Intention-to-treat analysis showed reductions in insomnia severity in both groups [MBTI: Cohen's effect size d = -1.27, 95% confidence interval (CI) -1.61 to -0.89; SHEEP: d = -0.69, 95% CI -0.96 to -0.43], with significantly greater improvement in MBTI. Sleep quality improved equivalently in both groups (MBTI: d = -1.19; SHEEP: d = -1.02). No significant interaction effects were observed in objective sleep measures. However, only MBTI had reduced WASO_actigraphy (MBTI: d = -0.30; SHEEP: d = 0.02), SOL_actigraphy (MBTI: d = -0.25; SHEEP: d = -0.09), and WASO_PSG (MBTI: d = -0.26; SHEEP (d = -0.18). There was no change in SOL_PSG. No participants withdrew because of adverse effects.

CONCLUSIONS

MBTI is effective at improving subjective and objective sleep quality in older adults, and could be a valid alternative for persons who have failed or do not have access to standard frontline therapies.

Working-from-home persistently influences sleep and physical activity 2 years after the Covid-19 pandemic onset: a longitudinal sleep tracker and electronic diary-based study

Objective

Working from home (WFH) has become common place since the Covid-19 pandemic. Early studies observed population-level shifts in sleep patterns (later and longer sleep) and physical activity (reduced PA), during home confinement. Other studies found these changes to depend on the proportion of days that individuals WFH (vs. work from office; WFO). Here, we examined the effects of WFH on sleep and activity patterns in the transition to normality during the later stages of the Covid-19 pandemic (Aug 2021-Jan 2022).

Methods

Two-hundred and twenty-five working adults enrolled in a public health study were followed for 22  weeks. Sleep and activity data were collected with a consumer fitness tracker (Fitbit Versa 2). Over three 2-week periods (Phase 1/week 1-2: August 16-29, 2021; Phase 2/week 11-12: October 25-November 7, 2021; Phase 3/week 21-22: January 3-16, 2022), participants provided daily Fitbit sleep and activity records. Additionally, they completed daily phone-based ecological momentary assessment (EMA), providing ratings of sleep quality, wellbeing (mood, stress, motivation), and information on daily work arrangements (WFH, WFO, no work). Work arrangement data were used to examine the effects of WFH vs. WFO on sleep, activity, and wellbeing.

Results

The proportion of WFH vs. WFO days fluctuated over the three measurement periods, mirroring evolving Covid restrictions. Across all three measurement periods WFH days were robustly associated with later bedtimes (+14.7 min), later wake times (+42.3 min), and longer Total Sleep Time (+20.2 min), compared to WFO days. Sleep efficiency was not affected. WFH was further associated with lower daily step count than WFO (-2,471 steps/day). WFH was associated with higher wellbeing ratings compared to WFO for those participants who had no children. However, for participants with children, these differences were not present.

Conclusion

Pandemic-initiated changes in sleep and physical activity were sustained during the later stage of the pandemic. These changes could have longer term effects, and conscious effort is encouraged to harness the benefits (i.e., longer sleep), and mitigate the pitfalls (i.e., less physical activity). These findings are relevant for public health as hybrid WHF is likely to persist in a post-pandemic world.

A Randomised Controlled Trial of a Digital, Small Incentive-based Intervention for Working Adults with Short Sleep

Study Objectives

We evaluated the efficacy of a digitally-delivered, small and scalable incentive-based intervention program on sleep and wellbeing in short-sleeping, working adults.

Methods

A 22-week, parallel-group, randomised controlled trial was conducted on 21-40y participants gifted with Fitbit TM devices to measure sleep for 2+ years, as part of a broader healthy lifestyle study. 225 short sleepers (141 males; average time-in-bed, TIB&lt;7h) were randomly assigned in a 2:1 ratio to Goal-Setting or Control groups. The Goal-Setting group received health vouchers (~USD 0.24) for meeting each sleep goal (i.e. increasing weeknight TIB by 30 mins / sleeping before midnight).The study spanned 3 Phases: 1) 2-week Baseline, 2) 10-week Intervention, and 3) 10-week Follow-Up. Wellbeing questionnaires were administered on Weeks 1-2, 11-12 and 21-22.

Results

Baseline weeknight TIB (mean±SD) was 387±43 min (Goal-Setting) and 399±44 min (Control), while bedtime was 00:53±01:13 (Goal-Setting), and 00:38±00:56 (Control). No difference in sleep outcomes were observed at study endpoints, but exploratory week-by-week analysis showed that on Weeks 3-5, TIB in the Goal-Setting group increased (9-18 min; ps&lt;0.05) while on Week 5, bedtimes shifted earlier (15 min; p&lt;0.01) compared to Baseline. Morning sleepiness was reduced in the Goal-Setting group (mean(SEM)=-3.17(1.53); p=0.04). Between-group differences were not significant (p=0.62). Main barriers to sleeping longer were work hours (35%), followed by leisure activities (23%) and family commitments (22%).

Conclusion

Our program resulted in encouraging subjective sleep improvements and short-term sleep extension but sustained transformation of sleep will probably require structural measures to overcome significant obstacles to sleep.

Predicting vigilance vulnerability during 1 and 2 weeks of sleep restriction with baseline performance metrics

Study Objectives

We attempted to predict vigilance performance in adolescents during partial sleep deprivation using task summary metrics and drift diffusion modelling measures (DDM) derived from baseline vigilance performance.

Methods

In the Need for Sleep studies, 57 adolescents (age = 15-19 years) underwent two baseline nights of 9-h time-in-bed (TIB), followed by two cycles of weekday sleep-restricted nights (5-h or 6.5-h TIB) and weekend recovery nights (9-h TIB). Vigilance was assessed daily with the Psychomotor Vigilance Task (PVT), with the number of lapses (response times ≥ 500 ms) as the primary outcome measure. The two DDM predictors were drift rate, which quantifies the speed of information accumulation and determines how quickly an individual derives a decision response, and non-decision time range, which indicates within-subject variation in physical, non-cognitive responding, e.g. motor actions.

Results

In the first week of sleep curtailment, faster accumulation of lapses was significantly associated with more lapses at baseline (p = .02), but not the two baseline DDM metrics: drift and non-decision time range (p > .07). On the other hand, faster accumulation of lapses and greater increment in reaction time variability from the first to the second week of sleep restriction were associated with lower drift (p < .007) at baseline.

Conclusions

Among adolescents, baseline PVT lapses can predict inter-individual differences in vigilance vulnerability during 1 week of sleep restriction on weekdays, while drift more consistently predicts vulnerability during more weeks of sleep curtailment.

Clinical Trial Information

Effects of Napping in Sleep-Restricted Adolescents, clinicaltrials.gov, NCT02838095. The Cognitive and Metabolic Effects of Sleep Restriction in Adolescents (NFS4), clinicaltrials.gov, NCT03333512.

An automated heart rate-based algorithm for sleep stage classification: Validation using conventional polysomnography and an innovative wearable electrocardiogram device

Background

The rapid advancement in wearable solutions to monitor and score sleep staging has enabled monitoring outside of the conventional clinical settings. However, most of the devices and algorithms lack extensive and independent validation, a fundamental step to ensure robustness, stability, and replicability of the results beyond the training and testing phases. These systems are thought not to be feasible and reliable alternatives to the gold standard, polysomnography (PSG).

Materials and methods

This validation study highlights the accuracy and precision of the proposed heart rate (HR)-based deep-learning algorithm for sleep staging. The illustrated solution can perform classification at 2-levels (Wake; Sleep), 3-levels (Wake; NREM; REM) or 4- levels (Wake; Light; Deep; REM) in 30-s epochs. The algorithm was validated using an open-source dataset of PSG recordings (Physionet CinC dataset, n = 994 participants, 994 recordings) and a proprietary dataset of ECG recordings (Z3Pulse, n = 52 participants, 112 recordings) collected with a chest-worn, wireless sensor and simultaneous PSG collection using SOMNOtouch.

Results

We evaluated the performance of the models in both datasets in terms of Accuracy (A), Cohen's kappa (K), Sensitivity (SE), Specificity (SP), Positive Predictive Value (PPV), and Negative Predicted Value (NPV). In the CinC dataset, the highest value of accuracy was achieved by the 2-levels model (0.8797), while the 3-levels model obtained the best value of K (0.6025). The 4-levels model obtained the lowest SE (0.3812) and the highest SP (0.9744) for the classification of Deep sleep segments. AHI and biological sex did not affect scoring, while a significant decrease of performance by age was reported across the models. In the Z3Pulse dataset, the highest value of accuracy was achieved by the 2-levels model (0.8812), whereas the 3-levels model obtained the best value of K (0.611). For classification of the sleep states, the lowest SE (0.6163) and the highest SP (0.9606) were obtained for the classification of Deep sleep segment.

Conclusion

The results of the validation procedure demonstrated the feasibility of accurate HR-based sleep staging. The combination of the proposed sleep staging algorithm with an inexpensive HR device, provides a cost-effective and non-invasive solution deployable in the home environment and robust across age, sex, and AHI scores.

Higher long-term mortality in patients with concomitant acute coronary syndrome and aortic stenosis

Background

Aortic stenosis (AS) and acute coronary syndrome (ACS) share similar cardiovascular risk factors, and their concomitant presentation is increasing in incidence with the aging population. Yet literature regarding the prognosis of patients with concomitant ACS and AS remains scarce.

Methods

This retrospective cohort study examined consecutive patients presenting with ACS (ST-segment elevation myocardial infarction [STEMI] and non-STEMI [NSTEMI]) and concomitant AS between 1 January 2011 and 31 March 2021 in a tertiary hospital. The cohort was divided into mild, moderate and severe AS based on index echocardiogram. The primary outcome was all-cause mortality. Kaplan-Meier curves were constructed to compare all-cause mortality among the three groups of patients, based on ACS type and left ventricular ejection fraction (LVEF). Multivariable Cox regression was performed to identify independent predictors of all-cause mortality.

Results

Of a total of 563 patients, 264 had mild (46.9%), 193 moderate (34.3%) and 106 severe AS (18.8%). The mean follow-up duration was 2.5 (± 2.4) years. Majority of patients (72.5%) presented with NSTEMI. Patients with moderate and severe AS had higher rates of all-cause mortality compared to those with mild AS (49.7% vs. 51.4% vs. 35.6% respectively, p=0.002). Concomitant moderate (HR 1.439, 95% CI 1.012–2.048, p=0.043) and severe AS (HR 1.844, 95% CI 1.159–2.933, p=0.010) were independent predictors of all-cause mortality after adjusting for age, gender, LVEF, ACS type, chronic kidney disease, diabetes, hypertension, coronary artery bypass grafting and aortic valve replacement as a time-dependent variable. The Kaplan-Meier curves demonstrated excess mortality in moderate and severe AS, compared to the mild AS group (p&lt;0.001), with similar survival trends observed in the STEMI and the NSTEMI groups, as well as those with preserved LVEF.

Conclusion

Regardless of the ACS presentation type, long-term excess mortality in those with concomitant moderate or severe AS was observed. The adverse prognosis typically observed in patients with concomitant severe AS, in the setting of ACS, extends to patients with moderate AS.

Funding Acknowledgement

Type of funding sources: None.

Minimum number of nights for reliable estimation of habitual sleep using a consumer sleep tracker

Study Objectives

To determine the minimum number of nights required to reliably estimate weekly and monthly mean sleep duration and sleep variability measures from a consumer sleep technology (CST) device (Fitbit).

Methods

Data comprised 107 144 nights from 1041 working adults aged 21-40 years. Intraclass correlation (ICC) analyses were conducted on both weekly and monthly time windows to determine the number of nights required to achieve ICC values of 0.60 and 0.80, corresponding to "good" and "very good" reliability thresholds. These minimum numbers were then validated on data collected 1-month and 1-year later.

Results

Minimally, 3 and 5 nights were required to obtain "good" and "very good" mean weekly total sleep time (TST) estimates, while 5 and 10 nights were required for monthly TST estimates. For weekday-only estimates, 2 and 3 nights were sufficient for weekly time windows while 3 and 7 nights sufficed for monthly time windows. Weekend-only estimates of monthly TST required 3 and 5 nights. TST variability required 5 and 6 nights for weekly time windows, and 11 and 18 nights for monthly time windows. Weekday-only weekly variability required 4 nights for both "good" and "very good" estimates while monthly variability required 9 and 14 nights. Weekend-only estimates of monthly variability required 5 and 7 nights. Error estimates made using data collected 1-month and 1-year later with these parameters were comparable to those associated with the original dataset.

Conclusions

Studies should consider the metric, measurement window of interest, and desired reliability threshold to decide on the minimum number of nights required to assess habitual sleep using CST devices.

Dissociable changes in sleep architecture with mindfulness and sleep hygiene intervention in older adults: secondary and exploratory analysis of polysomnography data from the Mindfulness Sleep Therapy (MIST) trial

OBJECTIVES

We conducted a secondary analysis of the Mindfulness Sleep Therapy study, a randomized controlled trial testing Mindfulness-Based Therapy for Insomnia (MBTI) against a sleep hygiene education and exercise program (SHEEP). We investigated whether the interventions led to changes in sleep macroarchitecture (N2, N3 and REM), and microarchitecture (sleep fragmentation, slow wave activity, spectral band power) measured by ambulatory polysomnography (PSG).

METHODS

48 MBTI and 46 SHEEP participants provided usable PSG and subjective sleep quality data both pre- and post intervention. The interventions consisted of 8 weekly 2-hour group sessions, and daily practice. PSG data were staged according to the American Academy of Sleep Medicine criteria by 2 technicians blind to time point and condition. Repeated-measures ANOVA and permutation analysis were used to test for differences over time and between the interventions.

RESULTS

Self-reported sleep quality improved in both study groups. We observed significant increases in N2 in MBTI but not SHEEP (p = .045), and significant increases in N3 in SHEEP but not MBTI (p = .012). No significant differences over time or between group were observed in N1, REM, or sleep fragmentation. Higher frequency non-REM EEG power decreased in SHEEP but not MBTI. Slow wave activity and slow wave activity dissipation did not differ over time or between groups. Among all variables, significant time by group interactions were observed in only N3 and non-REM alpha power.

CONCLUSIONS

MBTI and sleep hygiene education had different effects on sleep macro and microarchitecture, suggesting that the underlying mechanisms of mindfulness training in improving sleep quality may differ from traditional interventions.

A sleep schedule incorporating naps benefits the transformation of hierarchical knowledge

Study Objectives

The learning brain establishes schemas (knowledge structures) that benefit subsequent learning. We investigated how sleep and having a schema might benefit initial learning followed by rearranged and expanded memoranda. We concurrently examined the contributions of sleep spindles and slow-wave sleep to learning outcomes.

Methods

Fifty-three adolescents were randomly assigned to an 8 h Nap schedule (6.5 h nocturnal sleep with a 90-minute daytime nap) or an 8 h No-Nap, nocturnal-only sleep schedule. The study spanned 14 nights, simulating successive school weeks. We utilized a transitive inference task involving hierarchically ordered faces. Initial learning to set up the schema was followed by rearrangement of the hierarchy (accommodation) and hierarchy expansion (assimilation). The expanded sequence was restudied. Recall of hierarchical knowledge was tested after initial learning and at multiple points for all subsequent phases. As a control, both groups underwent a No-schema condition where the hierarchy was introduced and modified without opportunity to set up a schema. Electroencephalography accompanied the multiple sleep opportunities.

Results

There were main effects of Nap schedule and Schema condition evidenced by superior recall of initial learning, reordered and expanded memoranda. Improved recall was consistently associated with higher fast spindle density but not slow-wave measures. This was true for both nocturnal sleep and daytime naps.

Conclusion

A sleep schedule incorporating regular nap opportunities compared to one that only had nocturnal sleep benefited building of robust and flexible schemas, facilitating recall of the subsequently rearranged and expanded structured knowledge. These benefits appear to be strongly associated with fast spindles.

Clinical Trial registration

NCT04044885 (https://clinicaltrials.gov/ct2/show/NCT04044885).

Staying vigilant during recurrent sleep restriction: dose-response effects of time-in-bed and benefits of daytime napping

Study Objectives

We characterized vigilance deterioration with increasing time-on-task (ToT) during recurrent sleep restriction of different extents on simulated weekdays and recovery sleep on weekends, and tested the effectiveness of afternoon napping in ameliorating ToT-related deficits.

Methods

In the Need for Sleep studies, 194 adolescents (age = 15–19 years) underwent two baseline nights of 9-h time-in-bed (TIB), followed by two cycles of weekday manipulation nights and weekend recovery nights (9-h TIB). They were allocated 9 h, 8 h, 6.5 h, or 5 h of TIB for nocturnal sleep on weekdays. Three additional groups with 5 h or 6.5 h TIB were given an afternoon nap opportunity (5 h + 1 h, 5 h + 1.5 h, and 6.5 h + 1.5 h). ToT effects were quantified by performance change from the first 2 min to the last 2 min in a 10-min Psychomotor Vigilance Task administered daily.

Results

The 9 h and the 8 h groups showed comparable ToT effects that remained at baseline levels throughout the protocol. ToT-related deficits were greater among the 5 h and the 6.5 h groups, increased prominently in the second week of sleep restriction despite partial recuperation during the intervening recovery period and diverged between these two groups from the fifth sleep-restricted night. Daytime napping attenuated ToT effects when nocturnal sleep restriction was severe (i.e. 5-h TIB/night), and held steady at baseline levels for a milder dose of nocturnal sleep restriction when total TIB across 24 h was within the age-specific recommended sleep duration (i.e. 6.5 h + 1.5 h).

Conclusions

Reducing TIB beyond the recommended duration significantly increases ToT-associated vigilance impairment, particularly during recurrent periods of sleep restriction. Daytime napping is effective in ameliorating such decrement.

Clinical Trial Registration

NCT02838095, NCT03333512, and NCT04044885.

Multi-Night at-Home Evaluation of Improved Sleep Detection and Classification with a Memory-Enhanced Consumer Sleep Tracker

PURPOSE

To evaluate the benefits of applying an improved sleep detection and staging algorithm on minimally processed multi-sensor wearable data collected from older generation hardware.

PATIENTS AND METHODS

58 healthy, East Asian adults aged 23-69 years (M = 37.10, SD = 13.03, 32 males), each underwent 3 nights of PSG at home, wearing 2^nd Generation Oura Rings equipped with additional memory to store raw data from accelerometer, infra-red photoplethysmography and temperature sensors. 2-stage and 4-stage sleep classifications using a new machine-learning algorithm (Gen3) trained on a diverse and independent dataset were compared to the existing consumer algorithm (Gen2) for whole-night and epoch-by-epoch metrics.

RESULTS

Gen 3 outperformed its predecessor with a mean (SD) accuracy of 92.6% (0.04), sensitivity of 94.9% (0.03), and specificity of 78.5% (0.11); corresponding to a 3%, 2.8% and 6.2% improvement from Gen2 across the three nights, with Cohen's d values >0.39, t values >2.69, and p values <0.01. Notably, Gen 3 showed robust performance comparable to PSG in its assessment of sleep latency, light sleep, rapid eye movement (REM), and wake after sleep onset (WASO) duration. Participants <40 years of age benefited more from the upgrade with less measurement bias for total sleep time (TST), WASO, light sleep and sleep efficiency compared to those ≥40 years. Males showed greater improvements on TST and REM sleep measurement bias compared to females, while females benefitted more for deep sleep measures compared to males.

CONCLUSION

These results affirm the benefits of applying machine learning and a diverse training dataset to improve sleep measurement of a consumer wearable device. Importantly, collecting raw data with appropriate hardware allows for future advancements in algorithm development or sleep physiology to be retrospectively applied to enhance the value of longitudinal sleep studies.

Reopening after lockdown: The influence of working-from-home and digital device use on sleep, physical activity, and wellbeing following COVID-19 lockdown and reopening

Study Objectives

COVID-19 lockdowns drastically affected sleep, physical activity, and wellbeing. We studied how these behaviors evolved during reopening the possible contributions of continued working from home and smartphone usage.

Methods

Participants (N = 198) were studied through the lockdown and subsequent reopening period, using a wearable sleep/activity tracker, smartphone-delivered ecological momentary assessment (EMA), and passive smartphone usage tracking. Work/study location was obtained through daily EMA ascertainment.

Results

Upon reopening, earlier, shorter sleep and increased physical activity were observed, alongside increased self-rated stress and poorer evening mood ratings. These reopening changes were affected by post-lockdown work arrangements and patterns of smartphone usage. Individuals who returned to work or school in-person tended toward larger shifts to earlier sleep and wake timings. Returning to in-person work/school also correlated with more physical activity. Contrary to expectation, there was no decrease in objectively measured smartphone usage after reopening. A cluster analysis showed that persons with relatively heavier smartphone use prior to bedtime had later sleep timings and lower physical activity.

Conclusions

These observations indicate that the reopening after lockdown was accompanied by earlier sleep timing, increased physical activity, and altered mental wellbeing. Moreover, these changes were affected by work/study arrangements and smartphone usage patterns.

Cortical Thinning and Sleep Slow Wave Activity Reductions Mediate Age-Related Improvements in Cognition During Mid-Late Adolescence

Study Objectives

Gains in cognitive test performance that occur during adolescence are associated with brain maturation. Cortical thinning and reduced sleep slow wave activity (SWA) are markers of such developmental changes. Here we investigate whether they mediate age-related improvements in cognition.

Methods

109 adolescents aged 15–19 years (49 males) underwent magnetic resonance imaging, polysomnography (PSG), and a battery of cognitive tasks within a 2-month time window. Cognitive tasks assessed nonverbal intelligence, sustained attention, speed of processing and working memory and executive function. To minimize the effect of sleep history on SWA and cognitive performance, PSG and test batteries were administered only after at least 8 nights of 9-h time-in-bed (TIB) sleep opportunity.

Results

Age-related improvements in speed of processing (r = 0.33, p = 0.001) and nonverbal intelligence (r = 0.24, p = 0.01) domains were observed. These cognitive changes were associated with reduced cortical thickness, particularly in bilateral temporoparietal regions (rs = −0.21 to −0.45, ps < 0.05), as well as SWA (r = −0.35, p < 0.001). Serial mediation models found that ROIs in the middle/superior temporal cortices, together with SWA mediated the age-related improvement observed on cognition.

Conclusions

During adolescence, age-related improvements in cognition are mediated by reductions in cortical thickness and sleep SWA.

A longitudinal analysis of COVID-19 lockdown stringency on sleep and resting heart rate measures across 20 countries

Lockdowns imposed to stem the spread of COVID-19 massively disrupted the daily routines of many worldwide, but studies to date have been mostly confined to observations within a limited number of countries, based on subjective reports and surveys from specific time periods during the pandemic. We investigated associations between lockdown stringency and objective sleep and resting-heart rate measures in ~ 113,000 users of a consumer sleep tracker across 20 countries from Jan to Jul 2020, compared to an equivalent period in 2019. With stricter lockdown measures, midsleep times were universally delayed, particularly on weekdays, while midsleep variability and resting heart rate declined. These shifts (midsleep: + 0.09 to + 0.58 h; midsleep variability: − 0.12 to − 0.26 h; resting heart rate: − 0.35 to − 2.08 bpm) correlated with the severity of lockdown across different countries (all Ps < 0.001) and highlight the graded influence of stringency lockdowns on human physiology.

Memory performance following napping in habitual and non-habitual nappers

Study Objectives

Afternoon naps benefit memory but this may depend on whether one is a habitual napper (HN; ≥1 nap/week) or non-habitual napper (NN). Here, we investigated whether a nap would benefit HN and NN differently, as well as whether HN would be more adversely affected by nap restriction compared to NN.

Methods

Forty-six participants in the nap condition (HN-nap: n = 25, NN-nap: n = 21) took a 90-min nap (14:00–15:30 pm) on experimental days while 46 participants in the Wake condition (HN-wake: n = 24, NN-wake: n = 22) remained awake in the afternoon. Memory tasks were administered after the nap to assess short-term topographical memory and long-term memory in the form of picture encoding and factual knowledge learning respectively.

Results

An afternoon nap boosted picture encoding and factual knowledge learning irrespective of whether one habitually napped (main effects of condition (nap/wake): ps < 0.037). However, we found a significant interaction for the hippocampal-dependent topographical memory task (p = 0.039) wherein a nap, relative to wake, benefitted habitual nappers (HN-nap vs HN-wake: p = 0.003) compared to non-habitual nappers (NN-nap vs. NN-wake: p = 0.918). Notably for this task, habitual nappers’ performance significantly declined if they were not allowed to nap (HN-wake vs NN-wake: p = 0.037).

Conclusions

Contrary to concerns that napping may be disadvantageous for non-habitual nappers, we found that an afternoon nap was beneficial for long-term memory tasks even if one did not habitually nap. Naps were especially beneficial for habitual nappers performing a short-term topographical memory task, as it restored the decline that would otherwise have been incurred without a nap.

Clinical Trial Information

NCT04044885.

070 Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes

Introduction

Brief intrusions of unintended sleep can occur in various contexts, for example during resting-state fMRI scans. In addition to changes in neural activity, such microsleep episodes are also associated with shifts in respiration and heartrate. Here we investigated how these concurrent changes alter the dynamics of the BOLD signal in the brain and estimates of functional connectivity.

Methods

Ten participants underwent 6 runs of 20 minute resting-state fMRI scans with concurrent respiration, PPG and EEG recording. Realtime eye-closure monitoring combined with post eye-opening self-reports were used to identify microsleep episodes of different durations.

Results

During microsleep, sustained reductions were observed in arousal as assessed by EEG (ratio of alpha to delta and theta bands), as expected. In comparison, cortical BOLD signal exhibited more complex, temporally multiphasic changes which were consistent across different microsleep durations from 4 to 44s: (i) an initial sleep-onset dip reaching a nadir after ~6s, followed by (ii) an increase above wake baseline that plateaued till awakening. On awakening, (iii) a transient positive bump occurred up to 6s, followed by (iv) an undershoot below baseline lasting ~30s. While seen across the whole brain, these changes showed regional variations, e.g., the signal plateau in the thalamus remained below wake baseline. Sleep onset and awakening were also associated with respective reductions and increases in respiration and heart rate, which affect blood oxygen levels. Brain functional connectivity estimates were altered by the frequency of falling asleep, and this was not resolved by global signal regression.

Conclusion

Falling asleep and awakening are shown here to be associated with large, widespread BOLD signal changes consistent across varied durations of microsleep. These signal changes are intimately intertwined with shifts in respiration and heart rate, which are influenced by common brainstem nuclei controlling sleep. These autonomic contributions to ‘brain signal’ changes at microsleep onset and awakening are integral to sleep, and urge the integration of autonomic and central nervous system contributions to BOLD signal into frameworks for understanding brain function using fMRI. In addition, the correlation between frequency of microsleep and extent of altered functional connectivity highlight the need to minimize sleep during resting state scans.

Support (if any)

NMRC/STaR/015/2013

154 Cortical thickness and sleep slow wave activity mediates age-related improvements in cognition during late adolescence

Introduction

Adolescence is a period of rapid brain maturation, and studies have independently documented reductions in cortical thickness, reduced sleep slow wave activity (0.5-4Hz), and improved cognition as a child transitions into adulthood. In the present work, we investigate whether these factors interact in late adolescence.

Methods

114 adolescents aged 15-19y (52 males) underwent a structural MRI scan, polysomnography (PSG) and a series of cognitive tests assessing fluid intelligence, sustained attention, speed of processing and working memory. As sleep history has been known to affect EEG measures of slow wave activity, actigraphic recordings ensured that participants received 9h of night the week prior to the PSG session. Cognitive scores were combined to obtain a single measure of global cognition. For assessment of cortical thickness, the Freesurfer (v5.3) pipeline was used to obtain measures for all regions of interest from the Desikan-Killiany cortical atlas. Pearson correlations were conducted to independently confirm associations between aging and reductions in cortical thickness, slow wave activity and improved global cognition, controlling for sex. Finally, a serial mediation model (SPSS PROCESS Model 6) was performed to test the mediating role of cortical thickness and slow wave activity between aging and global cognition.

Results

Reductions in EEG sleep slow wave activity, cortical thickness and improved global cognition was observed with increasing age, likely representing synaptic pruning and a decrease in waking metabolic activity that contributes to increased overall neural efficiency. Regions in the temporal and parietal areas showed the steepest age-related reductions. In addition, the age-related improvement in cognition was found to be mediated by both cortical thinning as well as reduced SWA activity, particularly in the middle temporal cortex.

Conclusion

The adolescent brain undergoes rapid growth in preparation for adulthood. Cortical restructuring through pruning of neural circuits during this period is associated with reduced slow wave activity, mediating the age-related improvement in cognition. Future work should investigate whether insults to the brain during this critical period alters this trajectory.

Support (if any)

This work was supported by grants awarded to Michael Chee (NMRC/STaR/015/2013, NRF2016-SOL002-001 and the Far East Organization).

231 COVID-19 Lockdown Policies Across 20 Countries Modulate Sleep and Resting Heart Rate Measures

Introduction

Lockdowns imposed to stem the spread of COVID-19 have disrupted the lifestyles of many worldwide, but studies to date are mostly confined to observations within a limited number of countries, based on subjective reports and survey from a narrow time window. In the present study, we investigate associations between the severity of lockdown policies and objective sleep and resting-heart rate measures.

Methods

Data from 113,000 users of a consumer sleep tracker across 20 countries were gathered between Jan–Jul 2020 and compared with an equivalent period in 2019 as a control for naturally occurring seasonal fluctuations. Lockdown stringency was derived using scores from the Oxford Government Response Tracker. Multilevel growth curve models were used to quantify the effect of lockdown stringency on changes to sleep patterns (midsleep time and midsleep variability) and resting heart rate changes, and to predict changes in resting heart rate from changes to sleep patterns.

Results

Lockdown severity modulated the size of shifts in sleep midpoint and regularity during this period. Midsleep times were delayed in all countries during strict lockdowns, particularly on weekdays, while midsleep variability reduced. The largest shifts in midsleep time (+0.09 to +0.58 hours), midsleep variability (–0.12 to –0.26 hours) and resting heart rate (–0.35 to –2.08 bpm) occurred in April and May - when most countries imposed their strictest lockdown measures. In addition, multilevel modelling revealed that for each unit increase in stringency index, midsleep time was delayed by 0.96 min, midsleep variability decreased by 0.46 min and resting heart rate decreased by 0.06 bpm. Finally, in models predicting changes in resting heart rate from changes to sleep patterns, midsleep variability was shown to be the strongest predictor of resting heart rate, wherein an hour increase in the standard deviation of midsleep variability predicted a 5.12 increase in bpm, while an hour increase in midsleep time only predicted a 1.25 decrease in bpm.

Conclusion

Our findings demonstrate the utility of large-scale data from consumer wearables in providing population-level insights into how lockdown severity directly impacts sleep health during this pandemic period.

Support (if any)

Work conducted at NUS is supported by a grant awarded to Michael Chee (NMRC/STAR19may-0001).

274 Multimodal longitudinal sleep tracking combining wearable, smartphone tap analysis and electronic questionnaires

Introduction

The proliferation of wearable and smartphone technologies has enabled continuous monitoring of sleep using data from different channels (physiological [wearables], behavioural [phone usage] and ecological momentary assessment [EMA self-report]). As these modalities use different methods to assess sleep, information gaps suggested by discrepancies between estimates may be filled in through cross-referencing among the modalities to produce a more accurate sleep measurement. Moreover, the pattern of discrepancies could inform about specific sleep and peri-sleep behaviors (e.g. phone use before bedtime).

Methods

198 staff and students from the National University of Singapore (61 male, mean age 26.15±5.83 years) were recruited for an 8-week study. Sleep timings were assessed daily from three modalities: a wearable sleep and activity tracker (Oura ring), estimations from smartphone touchscreen interactions (tappigraphy) and smartphone derived EMA self-reports. Sleep estimates from the different modalities were compared for agreement (bivariate correlation) and discrepancies (t-test). Additionally, clustering analysis of high-discrepancy nights (&gt;1h discrepancy between modalities) was performed to identify pattens of sleep behaviors that could lead to specific discrepancies.

Results

Adherence throughout the 8-week monitoring period (total 11,088 nights) was = high for the Oura ring; 9826 nights [80%]), Tappigraphy; 9740 nights [88%)), and EMA; 9166 nights [83%]). Sleep estimates across the three modalities showed high agreement (r=0.79-.91), with some discrepancies: Relative to self-report data, Oura wake time tended to be a later (Mean diff=9mins, t=18.58, p&lt;.001), while tappigraphy estimates of bedtime tended to be early (Mean diff=15mins, t=26.48, p&lt;.001). On 23% of nights (1755 nights), however, large discrepancies were detected (&gt;1h). K-means clustering identified three distinct patterns of discrepancy, which were dominantly expressed in different individuals. Group comparison revealed that these individuals differed in demographic variables (age, student/work status), sleep variables (sleep timing, duration, subjective sleepiness), and phone usage characteristics (overall and pre-bedtime phone usage).

Conclusion

These data show that the combined use of three streams of data concerning sleep is complementary. Moreover, discrepancy patterns provide specific insights into sleep and peri-sleep behaviors facilitating digital phenotyping.

Support (if any)

This research was supported by the National Medical Research Council Singapore (NMRC/STaR/015/2013 and NMRC/STaR19may-0001).

Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes

Falling asleep is common in fMRI studies. By using long eyelid closures to detect microsleep onset, we showed that the onset and termination of short sleep episodes invokes a systematic sequence of BOLD signal changes that are large, widespread, and consistent across different microsleep durations. The signal changes are intimately intertwined with shifts in respiration and heart rate, indicating that autonomic contributions are integral to the brain physiology evaluated using fMRI and cannot be simply treated as nuisance signals. Additionally, resting state functional connectivity (RSFC) was altered in accord with the frequency of falling asleep and in a manner that global signal regression does not eliminate. Our findings point to the need to develop a consensus among neuroscientists using fMRI on how to deal with microsleep intrusions. SIGNIFICANCE STATEMENT: Sleep, breathing and cardiac action are influenced by common brainstem nuclei. We show that falling asleep and awakening are associated with a sequence of BOLD signal changes that are large, widespread and consistent across varied durations of sleep onset and awakening. These signal changes follow closely those associated with deceleration and acceleration of respiration and heart rate, calling into question the separation of the latter signals as 'noise' when the frequency of falling asleep, which is commonplace in RSFC studies, correlates with the extent of RSFC perturbation. Autonomic and central nervous system contributions to BOLD signal have to be jointly considered when interpreting fMRI and RSFC studies.

A daytime nap restores hippocampal function and improves declarative learning

STUDY OBJECTIVES

Daytime naps can confer benefits on subsequent declarative learning, but the physiological correlates of this improvement are less well studied. We examined learning following a daytime nap compared with an equivalent waking period using fMRI and polysomnography.

METHODS

Forty healthy young adults who slept normally the previous night encoded word pair lists in an MRI scanner at 13:00 and 16:30. Between sessions, participants either stayed awake and watched a documentary (Wake Group; N = 20) or had a 90-minute nap opportunity (Nap Group; N = 20) monitored by polysomnography. Approximately 40 minutes after completing each encoding session, memory for learned words was assessed using cued-recall.

RESULTS

A significant Session × Group interaction effect (p < 0.001) was observed in which memory was significantly improved in the Nap but not in the Wake group (p < 0.001). There was also a Session × Run × Group interaction effect in the left hippocampus (p = 0.001), whereby activation during word pair encoding increased only following the nap. Both performance improvement (rs = 0.46, p = 0.04) and nap-related increase in hippocampal activation (rs = 0.46, p = 0.04) were correlated with nap spindle count (12-15 Hz) but not with slow oscillation power (p's ≥ 0.18).

CONCLUSIONS

After a habitual nocturnal sleep, participants who had a 90-minute afternoon nap encoded word pairs better than a comparable group who stayed awake. Increases in hippocampal activation following the nap suggest restored hippocampal function. Naptime spindles may contribute to improved memory.

Cognitive effects of split and continuous sleep schedules in adolescents differ according to total sleep opportunity

STUDY OBJECTIVES

We compared the basic cognitive functions of adolescents undergoing split (nocturnal sleep + daytime nap) and continuous nocturnal sleep schedules when total sleep opportunity was either below or within the recommended range (i.e. 6.5 or 8 h).

METHODS

Adolescent participants (age: 15-19 year) in the 8-h split (n = 24) and continuous (n = 29) sleep groups were compared with 6.5-h split and continuous sleep groups from a previous study (n = 58). These protocols involved two baseline nights (9-h time-in-bed [TIB]), 5 nights of sleep manipulation, 2 recovery nights (9-h TIB), followed by a second cycle of sleep manipulation (3 nights) and recovery (2 nights). Cognitive performance, subjective sleepiness, and mood were evaluated daily; sleep was assessed using polysomnography.

RESULTS

Splitting 6.5 h of sleep with a mid-afternoon nap offered a boost to cognitive function compared to continuous nocturnal sleep. However, when total TIB across 24 h increased to 8 h, the split and continuous sleep groups performed comparably in tests evaluating vigilance, working memory, executive function, processing speed, subjective sleepiness, and mood.

CONCLUSIONS

In adolescents, the effects of split sleep on basic cognitive functions vary by the amount of total sleep obtained. As long as the total sleep opportunity across 24 h is within the recommended range, students may fulfill sleep requirements by adopting a split sleep schedule consisting of a shorter period of nocturnal sleep combined with a mid-afternoon nap, without significant impact on basic cognitive functions.

CLINICAL TRIAL REGISTRATION

NCT04044885.

COVID-19-related mobility reduction: heterogenous effects on sleep and physical activity rhythms

STUDY OBJECTIVES

Mobility restrictions imposed to suppress transmission of COVID-19 can alter physical activity (PA) and sleep patterns that are important for health and well-being. Characterization of response heterogeneity and their underlying associations may assist in stratifying the health impact of the pandemic.

METHODS

We obtained wearable data covering baseline, incremental mobility restriction, and lockdown periods from 1,824 city-dwelling, working adults aged 21-40 years, incorporating 206,381 nights of sleep and 334,038 days of PA. Distinct rest-activity rhythm (RAR) profiles were identified using k-means clustering, indicating participants' temporal distribution of step counts over the day. Hierarchical clustering of the proportion of days spent in each of these RAR profiles revealed four groups who expressed different mixtures of RAR profiles before and during the lockdown.

RESULTS

Time in bed increased by 20 min during the lockdown without loss of sleep efficiency, while social jetlag measures decreased by 15 min. Resting heart rate declined by ~2 bpm. PA dropped an average of 42%. Four groups with different compositions of RAR profiles were found. Three were better able to maintain PA and weekday/weekend differentiation during lockdown. The least active group comprising ~51% of the sample, were younger and predominantly singles. Habitually less active already, this group showed the greatest reduction in PA during lockdown with little weekday/weekend differences.

CONCLUSION

In the early aftermath of COVID-19 mobility restriction, PA appears to be more severely affected than sleep. RAR evaluation uncovered heterogeneity of responses to lockdown that could associate with different outcomes should the resolution of COVID-19 be protracted.

Multi-Night Validation of a Sleep Tracking Ring in Adolescents Compared with a Research Actigraph and Polysomnography

BACKGROUND

Wearable devices have tremendous potential for large-scale longitudinal measurement of sleep, but their accuracy needs to be validated. We compared the performance of the multisensor Oura ring (Oura Health Oy, Oulu, Finland) to polysomnography (PSG) and a research actigraph in healthy adolescents.

METHODS

Fifty-three adolescents (28 females; aged 15-19 years) underwent overnight PSG monitoring while wearing both an Oura ring and Actiwatch 2 (Philips Respironics, USA). Measurements were made over multiple nights and across three levels of sleep opportunity (5 nights with either 6.5 or 8h, and 3 nights with 9h). Actiwatch data at two sensitivity settings were analyzed. Discrepancies in estimated sleep measures as well as sleep-wake, and sleep stage agreements were evaluated using Bland-Altman plots and epoch-by-epoch (EBE) analyses.

RESULTS

Compared with PSG, Oura consistently underestimated TST by an average of 32.8 to 47.3 minutes (Ps < 0.001) across the different TIB conditions; Actiwatch 2 at its default setting underestimated TST by 25.8 to 33.9 minutes. Oura significantly overestimated WASO by an average of 30.7 to 46.3 minutes. It was comparable to Actiwatch 2 at default sensitivity in the 6.5, and 8h TIB conditions. Relative to PSG, Oura significantly underestimated REM sleep (12.8 to 19.5 minutes) and light sleep (51.1 to 81.2 minutes) but overestimated N3 by 31.5 to 46.8 minutes (Ps < 0.01). EBE analyses demonstrated excellent sleep-wake accuracies, specificities, and sensitivities - between 0.88 and 0.89 across all TIBs.

CONCLUSION

The Oura ring yielded comparable sleep measurement to research grade actigraphy at the latter's default settings. Sleep staging needs improvement. However, the device appears adequate for characterizing the effect of sleep duration manipulation on adolescent sleep macro-architecture.

Differential effects of split and continuous sleep on neurobehavioral function and glucose tolerance in sleep-restricted adolescents

Study Objectives

Many adolescents are exposed to sleep restriction on school nights. We assessed how different apportionment of restricted sleep (continuous vs. split sleep) influences neurobehavioral function and glucose levels.

Methods

Adolescents, aged 15–19 years, were evaluated in a dormitory setting using a parallel-group design. Following two baseline nights of 9-hour time-in-bed (TIB), participants underwent either 5 nights of continuous 6.5-h TIB (n = 29) or 5-hour nocturnal TIB with a 1.5-hour afternoon nap (n = 29). After two recovery nights of 9-hour TIB, participants were sleep restricted for another three nights. Sleep was assessed using polysomnography (PSG). Cognitive performance and mood were evaluated three times per day. Oral glucose tolerance tests (OGTT) were conducted on mornings after baseline sleep, recovery sleep, and the third day of each sleep restriction cycle.

Results

The split sleep group had fewer vigilance lapses, better working memory and executive function, faster processing speed, lower level of subjective sleepiness, and more positive mood, even though PSG-verified total sleep time was less than the continuous sleep group. However, vigilance in both sleep-restricted groups was inferior to adolescents in a prior sample given 9-hour nocturnal TIB. During both cycles of sleep restriction, blood glucose during the OGTT increased by a greater amount in the split sleep schedule compared with persons receiving 6.5-hour continuous sleep.

Conclusions

In adolescents, modest multinight sleep restriction had divergent negative effects on cognitive performance and glucose levels depending on how the restricted sleep was apportioned. They are best advised to obtain the recommended amount of nocturnal sleep.

Trial registration

https://clinicaltrials.gov/ct2/show/NCT03333512

A split sleep schedule rescues short-term topographical memory after multiple nights of sleep restriction

Study Objectives

Chronic sleep restriction in adolescents is widespread, yet we know little about how to apportion the limited amount of sleep obtained to minimize cognitive impairment: should sleep occur only nocturnally, or be split across separate nocturnal and daytime nap periods? This is particularly relevant to hippocampal-dependent cognitive functions that underpin several aspects of learning.

Method

We assessed hippocampal function in four groups by evaluating short-term topographical memory with the Four Mountains Test (4MT). All participants began with 9 hours nocturnal time-in-bed (TIB) for 2 days before following different sleep schedules over the next 3 days. Each day, one group had 5 hours nocturnal TIB (5.0h; n = 30), another, 6.5 hours nocturnal TIB (6.5h; n = 29), and a third had 6.5 hours split into 5 hours nocturnal TIB and a 1.5 hour TIB daytime nap (5.0 + 1.5h; n = 29). A control group maintained 9 hours nocturnal TIB (9.0h; n = 30). The 4MT was administered mid-afternoon (1.5 hours after awakening for those who napped).

Results

Performance of the 5.0h and 6.5h nocturnal TIB groups was significantly impaired relative to the 9.0h control group. Performance of participants on the split- sleep schedule (5.0 + 1.5h) did not significantly differ from controls.

Conclusions

These findings suggest that hippocampal function is sensitive to moderate multi-night sleep restriction, but deficits can be ameliorated by splitting sleep, at least for a period after waking from a daytime nap. While this split sleep schedule should not be considered a replacement for adequate nocturnal sleep, it appears to benefit the cognitive and neurophysiological functions that underpin learning in those who are chronically sleep deprived.

Validation of a Consumer Sleep Wearable Device With Actigraphy and Polysomnography in Adolescents Across Sleep Opportunity Manipulations

STUDY OBJECTIVES

To compare the quality and consistency in sleep measurement of a consumer wearable device and a research-grade actigraph with polysomnography (PSG) in adolescents.

METHODS

Fifty-eight healthy adolescents (aged 15-19 years; 30 males) underwent overnight PSG while wearing both a Fitbit Alta HR and a Philips Respironics Actiwatch 2 (AW2) for 5 nights, with either 5 hours or 6.5 hours time in bed (TIB) and for 4 nights with 9 hours TIB. AW2 data were evaluated using two different wake and immobility thresholds. Discrepancies in estimated total sleep time (TST) and wake after sleep onset (WASO) between devices and PSG, as well as epoch-by-epoch agreements in sleep/wake classification, were assessed. Fitbit-generated sleep staging was compared to PSG.

RESULTS

Fitbit and AW2 under default settings similarly underestimated TST and overestimated WASO (TST: medium setting (M10) ≤ 38 minutes, Fitbit ≤ 47 minutes; WASO: M10 ≤ 38 minutes; Fitbit ≤ 42 minutes). AW2 at the high motion threshold setting provided readings closest to PSG (TST: ≤ 12 minutes; WASO: ≤ 18 minutes). Sensitivity for detecting sleep was ≥ 90% for both wearable devices and further improved to 95% by using the high threshold (H5) setting for the AW2 (0.95). Wake detection specificity was highest in Fitbit (≥ 0.88), followed by the AW2 at M10 (≥ 0.80) and H5 thresholds (≤ 0.73). In addition, Fitbit inconsistently estimated stage N1 + N2 sleep depending on TIB, underestimated stage N3 sleep (21-46 min), but was comparable to PSG for rapid eye movement sleep. Fitbit sensitivity values for the detection of N1 + N2, N3 and rapid eye movement sleep were ≥ 0.68, ≥ 0.50, and ≥ 0.72, respectively.

CONCLUSIONS

A consumer-grade wearable device can measure sleep duration as well as a research actigraph. However, sleep staging would benefit from further refinement before these methods can be reliably used for adolescents.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Title: The Cognitive and Metabolic Effects of Sleep Restriction in Adolescents; Identifier: NCT03333512; URL: https://clinicaltrials.gov/ct2/show/NCT03333512.

CITATION

Lee XK, Chee NIYN, Ong JL, Teo TB, van Rijn E, Lo JC, Chee MWL. Validation of a consumer sleep wearable device with actigraphy and polysomnography in adolescents across sleep opportunity manipulations. J Clin Sleep Med. 2019;15(9):1337-1346.

Does splitting sleep improve long-term memory in chronically sleep deprived adolescents?

Sleep aids the encoding and consolidation of declarative memories, but many adolescents do not obtain the recommended amount of sleep each night. After a normal night of sleep, there is abundant evidence that a daytime nap enhances the consolidation of material learned before sleep and also improves the encoding of new information upon waking. However, it remains unclear how learning is affected when sleep is split between nocturnal and daytime nap periods during a typical school week of restricted sleep. We compared long-term memory in 58 adolescents who underwent two simulated school weeks of suboptimal continuous (6.5 h nocturnal sleep opportunity) or split sleep (5 h nocturnal sleep +1.5 h daytime nap at 14:00). In the first week, participants encoded pictures in the late afternoon on Day 5 and were tested after 2-nights of recovery sleep. On 3 consecutive days in the second week, participants learned about six species of amphibians in the morning, and six different amphibians in the late afternoon. Testing was performed in the evening following a night of recovery sleep. In the first week, the split sleep group recognized more pictures. In the second week, they remembered more facts about species learned in the afternoon. Groups did not differ for species learned in the morning. This suggests that under conditions of sleep restriction, a split sleep schedule benefits learning after a nap opportunity without impairing morning learning, despite less preceding nocturnal sleep. While not replacing adequate nocturnal sleep, a split sleep schedule may be beneficial for chronically sleep restricted learners.

An end-to-end framework for real-time automatic sleep stage classification

Sleep staging is a fundamental but time consuming process in any sleep laboratory. To greatly speed up sleep staging without compromising accuracy, we developed a novel framework for performing real-time automatic sleep stage classification. The client–server architecture adopted here provides an end-to-end solution for anonymizing and efficiently transporting polysomnography data from the client to the server and for receiving sleep stages in an interoperable fashion. The framework intelligently partitions the sleep staging task between the client and server in a way that multiple low-end clients can work with one server, and can be deployed both locally as well as over the cloud. The framework was tested on four datasets comprising ≈1700 polysomnography records (≈12000 hr of recordings) collected from adolescents, young, and old adults, involving healthy persons as well as those with medical conditions. We used two independent validation datasets: one comprising patients from a sleep disorders clinic and the other incorporating patients with Parkinson’s disease. Using this system, an entire night’s sleep was staged with an accuracy on par with expert human scorers but much faster (≈5 s compared with 30–60 min). To illustrate the utility of such real-time sleep staging, we used it to facilitate the automatic delivery of acoustic stimuli at targeted phase of slow-sleep oscillations to enhance slow-wave sleep.

Trait-like characteristics of sleep EEG power spectra in adolescents across sleep opportunity manipulations

The electroencephalographic power spectra of non-rapid eye movement sleep in adults demonstrate trait-like consistency within participants across multiple nights, even when prior sleep deprivation is present. Here, we examined the extent to which this finding applies to adolescents who are habitually sleep restricted on school-days and sleep longer on weekends. We evaluated 78 adolescents across three sleep restriction groups who underwent different permutations of adequate sleep (9 hr time-in-bed), sleep restriction (5 hr time-in-bed), afternoon naps (1 hr afternoon) and recovery sleep (9 hr time-in-bed) that simulate behaviour on school-days and weekends. The control group comprised a further 22 adolescents who had 9 hr of sleep opportunity each night. Intra-class correlation coefficients showed moderate to almost perfect within-subject stability in electroencephalographic power spectra across multiple nights in both sleep restriction and control groups, even when changes to sleep macrostructure were observed. While nocturnal intra-class correlation metrics were lower in the low-frequency and spindle frequency bins in the sleep restriction compared with the control group, hierarchical clustering measures could still identify multi-night electroencephalographic spectra as originating from the same individual. The trait-like characteristics of electroencephalographic spectra from an adolescent remain identifiable despite the disruptive effects of multi-night sleep restriction to sleep architecture.

Auditory stimulation of sleep slow oscillations modulates subsequent memory encoding through altered hippocampal function

Study Objectives

Slow oscillations (SO) during sleep contribute to the consolidation of learned material. How the encoding of declarative memories during subsequent wakefulness might benefit from their enhancement during sleep is less clear. In this study, we investigated the impact of acoustically enhanced SO during a nap on subsequent encoding of declarative material.

Methods

Thirty-seven healthy young adults were studied under two conditions: stimulation (STIM) and no stimulation (SHAM), in counter-balanced order following a night of sleep restriction (4 hr time-in-bed [TIB]). In the STIM condition, auditory tones were phase-locked to the SO up-state during a 90 min nap opportunity. In the SHAM condition, corresponding time points were marked but tones were not presented. Thirty minutes after awakening, participants encoded pictures while undergoing fMRI. Picture recognition was tested 60 min later.

Results

Acoustic stimulation augmented SO across the group, but there was no group level benefit on memory. However, the magnitude of SO enhancement correlated with greater recollection. SO enhancement was also positively correlated with hippocampal activation at encoding. Although spindle activity increased, this did not correlate with memory benefit or shift in hippocampal signal.

Conclusions

Acoustic stimulation during a nap can benefit encoding of declarative memories. Hippocampal activation positively correlated with SO augmentation.

EEG Changes Accompanying Successive Cycles of Sleep Restriction With and Without Naps in Adolescents

Study objectives

To investigate the temporal evolution of sleep EEG changes in adolescents across two cycles of sleep restriction and recovery simulating an intense school week and to examine the effect of an afternoon nap on nocturnal sleep.

Methods

A parallel-group design, quasi-laboratory study was conducted in a student hostel. Fifty-seven adolescents (31 males, age = 15-19 years) were randomly assigned to nap or no nap groups. Participants underwent a 15-day protocol comprising two sleep restriction (5-hour time-in-bed [TIB]) and recovery (9-hour TIB) cycles. The nap group was also provided with a 1-hour nap opportunity at 14:00 following each sleep restriction night. Polysomnography recordings were obtained on nine nights and five nap episodes.

Results

Naps reduced homeostatic sleep pressure on sleep restriction nights as evidenced by longer N2 latency and reduced total sleep time (TST), sleep efficiency (SE), and slow wave energy. Sleep debt accumulated in both groups, evidenced by increased TST, greater SE, and reduced wake after sleep onset on recovery compared to baseline nights. Changes were greater in the no nap group. Recovery sleep after the first cycle of sleep restriction did not restore sleep architecture to baseline in either group. SE, rapid eye movement (REM), and non-REM sleep increased, and N2 latency was reduced in the second sleep restriction period.

Conclusions

Changes in sleep EEG induced by sleep restriction to 5-hour TIB for five nights were not eliminated after two nights of 9-hour recovery sleep. An afternoon nap helped but residual effects on the sleep EEG suggest that there is no substitute for adequate nocturnal sleep.

Influence of Post-deposition Heating Time and the Presence of Water Vapor on Sputter-coated Calcium Phosphate Crystallinity

Extensive research suggested that calcium phosphate (CaP) coatings on titanium implants are essential for early bone response. However, the characterization of CaP crystallinity and the means to control coating crystallinity are not well-established. In this study, the effect of a 400°C heat treatment for 1, 2, or 4 hours, and in the presence or absence of water vapor, on CaP crystallinity was investigated. Scanning electron microscopy indicated dense as-sputtered coatings. Increase in coating crystallinity was observed to be consistent with the increasing number of PO4 peaks observed as a result of different heat treatments. In addition, x-ray diffraction analyses indicated amorphous as-sputtered coatings, whereas crystalline CaP coatings in the range of 0-85% were observed after different post-deposition heat treatments. It was concluded that the presence of water vapor and post-deposition heat treatment time significantly affect the crystallinity of CaP coatings, which may ultimately affect bone healing.

EEG Changes across Multiple Nights of Sleep Restriction and Recovery in Adolescents: The Need for Sleep Study

STUDY OBJECTIVES

To investigate sleep EEG changes in adolescents across 7 nights of sleep restriction to 5 h time in bed [TIB]) and 3 recovery nights of 9 h TIB.

METHODS

A parallel-group design, quasi-laboratory study was conducted in a boarding school. Fifty-five healthy adolescents (25 males, age = 15-19 y) who reported habitual TIBs of approximately 6 h on week nights (group average) but extended their sleep on weekends were randomly assigned to Sleep Restriction (SR) or Control groups. Participants underwent a 2-week protocol comprising 3 baseline nights (TIB = 9 h), 7 nights of sleep opportunity manipulation (TIB = 5 h for the SR and 9 h for the Control group), and 3 nights of recovery sleep (TIB = 9 h). Polysomnography was obtained on two baseline, three manipulation, and two recovery nights.

RESULTS

Across the sleep restriction nights, total SWS duration was preserved relative to the 9 h baseline sleep opportunity, while other sleep stages were reduced. Considering only the first 5 h of sleep opportunity, SR participants had reduced N1 duration and wake after sleep onset (WASO), and increased total sleep time (TST), rapid eye movement (REM) sleep, and slow wave sleep (SWS) relative to baseline. Total REM sleep, N2, and TST duration remained above baseline levels by the third recovery sleep episode.

CONCLUSIONS

In spite of preservation of SWS duration over multiple nights of sleep restriction, adolescents accustomed to curtailing nocturnal sleep on school day nights evidence residual effects on sleep macro-structure, even after three nights of recovery sleep. Older teenagers may not be as resilient to successive nights of sleep restriction as is commonly believed.

Cognitive Performance, Sleepiness, and Mood in Partially Sleep Deprived Adolescents: The Need for Sleep Study

STUDY OBJECTIVES

To investigate the effects of sleep restriction (7 nights of 5 h time in bed [TIB]) on cognitive performance, subjective sleepiness, and mood in adolescents.

METHODS

A parallel-group design was adopted in the Need for Sleep Study. Fifty-six healthy adolescents (25 males, age = 15-19 y) who studied in top high schools and were not habitual short sleepers were randomly assigned to Sleep Restriction (SR) or Control groups. Participants underwent a 2-w protocol consisting of 3 baseline nights (TIB = 9 h), 7 nights of sleep opportunity manipulation (TIB = 5 h for the SR and 9 h for the control groups), and 3 nights of recovery sleep (TIB = 9 h) at a boarding school. A cognitive test battery was administered three times each day.

RESULTS

During the manipulation period, the SR group demonstrated incremental deterioration in sustained attention, working memory and executive function, increase in subjective sleepiness, and decrease in positive mood. Subjective sleepiness and sustained attention did not return to baseline levels even after 2 recovery nights. In contrast, the control group maintained baseline levels of cognitive performance, subjective sleepiness, and mood throughout the study. Incremental improvement in speed of processing, as a result of repeated testing and learning, was observed in the control group but was attenuated in the sleep-restricted participants, who, despite two recovery sleep episodes, continued to perform worse than the control participants.

CONCLUSIONS

A week of partial sleep deprivation impairs a wide range of cognitive functions, subjective alertness, and mood even in high-performing high school adolescents. Some measures do not recover fully even after 2 nights of recovery sleep.

COMMENTARY

A commentary on this article appears in this issue on page 497.

Effects of phase-locked acoustic stimulation during a nap on EEG spectra and declarative memory consolidation

OBJECTIVES

Acoustic stimulation synchronized to slow waves (SWs) can enhance these sleep features and facilitate memory consolidation during nocturnal sleep. Here, we investigated whether a similar benefit could be accrued following stimulation during an afternoon nap. We also evaluated the event-related dynamics of associated EEG spectral changes and their correlation with memory performance.

METHODS

Sixteen healthy young adults (mean age: 22 ± 1.4 years; nine males) were studied under two conditions: stimulation (STIM) and no stimulation (SHAM), in counter-balanced order. In the STIM condition, acoustic stimulation was delivered using blocks of five tones, each phase-locked to the SW up-state during a 90-min nap opportunity. In the SHAM condition, these time points were marked, but tones were not presented. Prior to the nap, participants learned 40 semantically related word pairs and immediate recall was tested. A delayed recall test was administered 45 min after awakening.

RESULTS

Compared to the SHAM condition, acoustic stimulation increased SW amplitude, theta, and fast spindle activity and attenuated the forgetting of word pairs (p values < 0.05).

CONCLUSION

Phase-locked acoustic stimulation can promote sleep-dependent declarative memory during a daytime nap. This can be achieved by stimulation in Stage 2 and SWS without a requirement for high-amplitude slow wave detection.

Now you hear me, now you don't: eyelid closures as an indicator of auditory task disengagement

STUDY OBJECTIVES

Eyelid closures in fatigued individuals signify task disengagement in attention-demanding visual tasks. Here, we studied how varying degrees of eyelid closure predict responses to auditory stimuli depending on whether a participant is well rested or sleep deprived. We also examined time-on-task effects and how more and less vulnerable individuals differed in frequency of eye closures and lapses.

DESIGN

Six repetitions of an auditory vigilance task were performed in each of two sessions: rested wakefulness (RW) and total sleep deprivation (TSD) (order counterbalanced).

SETTING

Sleep laboratory.

PARTICIPANTS

Nineteen healthy young adults (mean age: 22 ± 2.8 y; 11 males).

INTERVENTION

Approximately 24 h of TSD.

MEASUREMENTS AND RESULTS

Eyelid closure was rated on a 9-point scale (1 = fully closed to 9 = fully opened) using video segments time-locked to the auditory event. Eyes-open trials predominated during RW, but different degrees of eye closure were uniformly distributed during TSD. The frequency of lapses (response time > 800 ms or nonresponses) to auditory stimuli increased dramatically with greater degrees of eye closure, but the association was strong only during TSD. There were significant within-run time-on-task effects on eye closure and auditory lapses that were exacerbated by TSD. Participants who had more auditory lapses during TSD (more vulnerable) had greater variability in their eyelid closures.

CONCLUSIONS

Eyelid closures are a strong predictor of auditory task disengagement in the sleep-deprived state but are less relevant during rested wakefulness. Individuals relatively more impaired in this auditory vigilance task during total sleep deprivation display oculomotor evidence for greater state instability.

From point to local neighborhood: polyp detection in CT colonography using geodesic ring neighborhoods

Existing polyp detection methods rely heavily on curvature-based characteristics to differentiate between lesions. These assume that the discrete triangulated surface mesh or volume closely approximates a smooth continuous surface. However, this is often not the case and because curvature is computed as a local feature and a second-order differential quantity, the presence of noise significantly affects its estimation. For this reason, a more global feature is required to provide an accurate description of the surface at hand. In this paper, a novel method incorporating a local neighborhood around the centroid of a surface patch is proposed. This is done using geodesic rings which accumulate curvature information in a neighborhood around this centroid. This geodesic-ring neighborhood approximates a single smooth, continuous surface upon which curvature and orientation estimation methods can be applied. A new global shape index, S is also introduced and computed. These curvature and orientation values will be used to classify the surface as either a bulbous polyp, ridge-like fold or semiplanar structure. Experimental results show that this method is promising (100% sensitivity, 100% specificity for lesions > 10 mm) for distinguishing between bulbous polyps, folds and planar-like structures in the colon.