PSG Validation of minute-to-minute scoring for sleep and wake periods in a consumer wearable device

Validity and reliability of the Oura Ring Generation 3 (Gen3) with Oura sleep staging algorithm 2.0 (OSSA 2.0) when compared to multi-night ambulatory polysomnography: A validation study of 96 participants and 421,045 epochs

PURPOSE

To evaluate the validity and the reliability of the Oura Ring Generation 3 (Gen3) with Oura Sleep Staging Algorithm 2.0 (OSSA 2.0) through multi-night polysomnography (PSG).

PARTICIPANTS AND METHODS

Participants were 96 generally healthy Japanese men and women aged between 20 and 70 years contributing with 421,045 30-s epochs. Sleep scoring was performed according to American Academy of Sleep Medicine criteria. Each participant could contribute with a maximum of three polysomnography (PSG) nights. Within-participant means were created for each sleep measure and paired t-tests were used to compare equivalent measures obtained from the PSG and Oura Rings (non-dominant and dominant hand). Agreement between sleep measures were assessed using Bland-Altman plots. Interrater reliability for epoch accuracy was determined by prevalence-adjusted and bias-adjusted kappa (PABAK).

RESULTS

The Oura Ring did not significantly differ from PSG for the measures time in bed, total sleep time, sleep onset latency, sleep period time, wake after sleep onset, time spent in light sleep, and time spent in deep sleep. Oura Rings worn on the non-dominant- and dominant-hand underestimated sleep efficiency by 1.1 %-1.5 % and time spent in REM sleep by 4.1-5.6 min. The Oura Ring had a sensitivity of 94.4 %-94.5 %, specificity of 73.0 %-74.6 %, a predictive value for sleep of 95.9 %-96.1 %, a predictive value for wake of 66.6 %-67.0 %, and accuracy of 91.7 %-91.8 %. PABAK was 0.83-0.84 and reliability was 94.8 %. Sleep staging accuracy ranged between 75.5 % (light sleep) and 90.6 % (REM sleep).

CONCLUSIONS

The Oura Ring Gen3 with OSSA 2.0 shows good agreement with PSG for global sleep measures and time spent in light and deep sleep.

Fatigued but not sleepy? An empirical investigation of the differentiation between fatigue and sleepiness in sleep disorder patients in a cross-sectional study

OBJECTIVE

Sleepiness and fatigue are common complaints among individuals with sleep disorders. The two concepts are often used interchangeably, causing difficulty with differential diagnosis and treatment decisions. The current study investigated sleep disorder patients to determine which factors best differentiated sleepiness from fatigue.

METHODS

The study used a subset of participants from a multi-site study (n = 606), using a cross-sectional study design. We selected 60 variables associated with either sleepiness or fatigue, including demographic, mental health, and lifestyle factors, medical history, sleep questionnaires, rest-activity rhythms (actigraphy), polysomnographic (PSG) variables, and sleep diaries. Fatigue was measured with the Fatigue Severity Scale and sleepiness was measured with the Epworth Sleepiness Scale. A Random Forest machine learning approach was utilized for analysis.

RESULTS

Participants' average age was 47.5 years (SD 14.0), 54.6% female, and the most common sleep disorder diagnosis was obstructive sleep apnea (67.4%). Sleepiness and fatigue were moderately correlated (r = 0.334). The model for fatigue (explained variance 49.5%) indicated depression was the strongest predictor (relative explained variance 42.7%), followed by insomnia severity (12.3%). The model for sleepiness (explained variance 17.9%), indicated insomnia symptoms was the strongest predictor (relative explained variance 17.6%). A post hoc receiver operating characteristic analysis indicated depression could be used to discriminate fatigue (AUC = 0.856) but not sleepiness (AUC = 0.643).

CONCLUSIONS

The moderate correlation between fatigue and sleepiness supports previous literature that the two concepts are overlapping yet distinct. Importantly, depression played a more prominent role in characterizing fatigue than sleepiness, suggesting depression could be used to differentiate the two concepts.

Stability and Volatility of Human Rest-Activity Rhythms: Insights from Very Long Actograms (VLAs)

Importance

Wrist-worn activity monitors provide biomarkers of health by non-obtrusively measuring the timing and amount of rest and physical activity (rest-activity rhythms, RARs). The morphology and robustness of RARs vary by age, gender, and sociodemographic factors, and are perturbed in various chronic illnesses. However, these are cross-sectionally derived associations from recordings lasting 4-10 days, providing little insights into how RARs vary with time.

Objective

To describe how RAR parameters can vary or evolve with time (~months).

Design Setting and Participants

48 very long actograms ("VLAs", ≥90 days in duration) were identified from subjects enrolled in the STAGES (Stanford Technology, Analytics and Genomics in Sleep) study, a prospective cross-sectional, multi-site assessment of individuals > 13 years of age that required diagnostic polysomnography to address a sleep complaint. A single 3-year long VLA (author GD) is also described.

Exposures/Intervention

None planned.

Main Outcomes and Measures

For each VLA, we assessed the following parameters in 14-day windows: circadian/ultradian spectrum, pseudo-F statistic ("F"), cosinor amplitude, intradaily variability, interdaily stability, acrophase and estimates of "sleep" and non-wearing.

Results

Included STAGES subjects (n = 48, 30 female) had a median age of 51, BMI of 29.4kg/m2, Epworth Sleepiness Scale score (ESS) of 10/24 and a median recording duration of 120 days. We observed marked within-subject undulations in all six RAR parameters, with many subjects displaying ultradian rhythms of activity that waxed and waned in intensity. When appraised at the group level (nomothetic), averaged RAR parameters remained remarkably stable over a ~4 month recording period. Cohort-level deficits in average RAR robustness associated with unemployment or high BMI (>29.4) also remained stable over time.

Conclusions and Relevance

Through an exemplary set of months-long wrist actigraphy recordings, this study quantitatively depicts the longitudinal stability and dynamic range of human rest-activity rhythms. We propose that continuous and long-term actigraphy may have broad potential as a holistic, transdiagnostic and ecologically valid monitoring biomarker of changes in chronobiological health. Prospective recordings from willing subjects will be necessary to precisely define contexts of use.

COVID-19 surveillance based on consumer wearable devices

Background

Consumer wearable devices such as wristbands and smartwatches have potential application value in communicable disease surveillance.

Objective

We investigated the ability of wearable devices to monitor COVID-19 patients of varying severity.

Methods

COVID-19 patients with mobile phones supporting wearable device applications were selected from Dalian Sixth People Hospital. Physiological parameters from the wearable devices and electronic questionnaires were collected from the device wearing until 14 days post-discharge. Clinical information during hospitalization was also recorded. Based on imaging data, the patients were categorized into the milder group without pneumonia and the more severe group with pneumonia. We plotted the curves of the physiological parameters of the two groups to compare the differences and changes.

Results

Ninety-eight patients were included in the analysis. The mean age was 39.6 ± 10.5 years, including 45 males (45.9%). There were 24 asymptomatic patients, 10 mild patients, 60 moderate patients, and 4 severe patients. Compared with the milder group, the more severe group had higher heart rate-related parameters, while the heart rate variability (HRV) was the opposite. In the more severe group, the heart rate-related parameters showed a downward trend from 0 to 7 days after the fever resolution. Among them, the resting heart rate and sleep heart rate decreased on the 25th day after the onset and were close to the milder group 1 week after discharge.

Conclusions

Consumer wearable devices have the potential to monitor respiratory infections. Heart rate-related parameters obtained from these devices can be sensitive indicators of COVID-19 severity and correlate with disease evolution.

Trial registration

ClinicalTrials.gov NCT04459637.

Objective and subjective sleep in patients with non-seasonal major depressive disorder and eveningness - Results from a randomized controlled trial of bright light therapy

STUDY OBJECTIVES

This study examines the (dis)agreement between objective and subjective sleep and their prospective changes in a randomized controlled trial of bright light therapy (BLT) in patients with major depressive disorder (MDD) and eveningness.

METHODS

A total of 93 adults were randomized to receive either 30-min daily of 10,000 lux BLT or 50lux placebo dim red light therapy (DRL group) for a total of 5 weeks. Actigraphic data were collected at the baseline and during the last week of treatment. (Dis)Concordance of diary and actigraphic sleep parameters were assessed by partial correlations and Bland-Altman plots, and the associations between these discrepancies to depression severity was assessed by linear regression models. Changes of sleep parameters were assessed by linear mixed models.

RESULTS

Significant correlations were found between subjective sleep timings and chronotype to actigraphic parameters. Discrepancies between diary- and actigraphic-measures were observed, and patients with more severe depressive symptoms were associated with a greater under-estimation of total sleep time (TST). A greater advance in the diary-based time to fall sleep and rise time were achieved in the BLT group as compared to the DRL group, while diary-based wake after sleep onset (WASO), TST and sleep efficiency (SE) comparably improved with time in both groups. There was no significant difference between the two groups in the actigraphic parameters after treatment.

CONCLUSIONS

In this study, we found that depression severity influenced subjective report of sleep. BLT led to a greater advance in subjective sleep timings when compared to the placebo group.

Consistency of chronotype measurements is affected by sleep quality, gender, longitude, and latitude

Chronotype has received increasing research attention. However, there remains some confusion about the influence of gender, age, sleep quality, insomnia severity, longitude, and latitude on the consistency of the chronotype measured by the different tools. Chronotype measurement indicators were collected from 421 participants. The midpoint of sleep for actigraphy (MSF_A), sleep diary (MSF_D), and Munich Chronotype Questionnaire (MCTQ) (MSFsc) on free days and the Morningness-Eveningness Questionnaire (rMEQ) scores were used to measure the chronotype. In addition, demographic information, Pittsburgh Sleep Quality Index (PSQI), and Insomnia Severity Index (ISI) were also collected. A significant correlation was identified between the questionnaires (MSF_D, MSFsc, rMEQ) and actigraphy (MSF_A) as measures of chronotype. MSF_A was associated with sleep latency and sleep disturbance in the PSQI subdimensions. The correlation between MS_D and sleep disturbance was significant. Both rMEQ and MSFsc were significantly correlated with PSQI (total scores and daytime dysfunction) and ISI. The consistency of all chronotype measurements for the questionnaires and actigraphy was influenced by gender. Among them, MSF_D is also affected by age, while only the latitude and sleep disturbance effect was found in the MSFsc. The influence of age, gender, sleep quality, and latitude should be emphasized when measuring the chronotype using self-reported methods.

Validity of Two Consumer Multisport Activity Tracker and One Accelerometer against Polysomnography for Measuring Sleep Parameters and Vital Data in a Laboratory Setting in Sleep Patients

Two commercial multisport activity trackers (Garmin Forerunner 945 and Polar Ignite) and the accelerometer ActiGraph GT9X were evaluated in measuring vital data, sleep stages and sleep/wake patterns against polysomnography (PSG). Forty-nine adult patients with suspected sleep disorders (30 males/19 females) completed a one-night PSG sleep examination followed by a multiple sleep latency test (MSLT). Sleep parameters, time in bed (TIB), total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), awake time (WASO + SOL), sleep stages (light, deep, REM sleep) and the number of sleep cycles were compared. Both commercial trackers showed high accuracy in measuring vital data (HR, HRV, SpO2, respiratory rate), r > 0.92. For TIB and TST, all three trackers showed medium to high correlation, r > 0.42. Garmin had significant overestimation of TST, with MAE of 84.63 min and MAPE of 25.32%. Polar also had an overestimation of TST, with MAE of 45.08 min and MAPE of 13.80%. ActiGraph GT9X results were inconspicuous. The trackers significantly underestimated awake times (WASO + SOL) with weak correlation, r = 0.11−0.57. The highest MAE was 50.35 min and the highest MAPE was 83.02% for WASO for Garmin and ActiGraph GT9X; Polar had the highest MAE of 21.17 min and the highest MAPE of 141.61% for SOL. Garmin showed significant deviations for sleep stages (p < 0.045), while Polar only showed significant deviations for sleep cycle (p = 0.000), r < 0.50. Garmin and Polar overestimated light sleep and underestimated deep sleep, Garmin significantly, with MAE up to 64.94 min and MAPE up to 116.50%. Both commercial trackers Garmin and Polar did not detect any daytime sleep at all during the MSLT test. The use of the multisport activity trackers for sleep analysis can only be recommended for general daily use and for research purposes. If precise data on sleep stages and parameters are required, their use is limited. The accuracy of the vital data measurement was adequate. Further studies are needed to evaluate their use for medical purposes, inside and outside of the sleep laboratory. The accelerometer ActiGraph GT9X showed overall suitable accuracy in detecting sleep/wake patterns.

Relationship Analogy between Sleep Bruxism and Temporomandibular Disorders in Children: A Narrative Review

Sleep bruxism (SB) is a condition characterized by repetitive clenching or grinding teeth and/or by bracing or thrusting of the mandible during sleep. Although SB is not considered a disorder in children, SB can be a potential physical and psychological hazard or consequence, and this study examines whether SB is a risk factor for TMD as it is in adults. A narrative review on the topic of inferring the relationship between sleep bruxism and TMD in children was performed based on a search in the PubMed and Google Scholar databases for articles published between 1999 and 2022. A total of 76 articles were included in this review. SB is very common in children, may be related to psychological distress or sleep breathing disorder, with a prevalence of up to 49%, and mainly occurs in the non-rapid eye movement stage in the sleep structure. SB may be one cause of TMD. The prevalence of TMD in children is 16–33%. Compared to the female-dominant TMD prevalence in adults, the sex-differences in TMD prevalence in children are less pronounced. However, TMD-related pain is more prevalent in girls than in boys. Given the complex etiology of each of SB and TMD in children, it can be inferred that the explanation of the relationship between the two conditions is very challenging. Ultimately, their relationship should be understood in the individual biopsychosocial model in the process of special physical growth and mental development of children. Moreover, appropriate clinical guidelines for a definitive diagnosis of SB and TMD in children and more research with a high scientific evidence level, which is comprehensive, considering physical, psychological, genetic, and social cultural factors, are required.

Association Between Nocturnal Sleep Duration and Obesity Indicators Among People with Type 2 Diabetes: A Cross-Sectional Study in Ningbo, China

AIM

The study aimed to investigate the association between the nocturnal sleep duration and five obesity indicators, namely, visceral fat area (VFA), subcutaneous fat area (SFA), bodyweight, body mass index (BMI) and waist circumference (WC), among people with type 2 diabetes mellitus (T2DM) in Ningbo, China.

METHODS

A cross-sectional study was conducted using the National Metabolic Management Centre (MMC) - Ningbo First Hospital data from 1st March 2018 to 28th February 2021. Adults with T2DM were included in the study. Simple and multiple (adjusted for sociodemographic and lifestyle factors and health conditions) linear regression analyses were performed to identify the associations.

RESULTS

In terms of VFA, SFA, bodyweight, BMI and WC, the eligibility criteria were satisfied by 2771, 2771, 2863, 2863 and 2862 patients, respectively. In the unadjusted model, the shorter nocturnal sleep duration was associated with higher VFA, SFA, bodyweight, BMI and WC. In other words, an hour increase in the nocturnal sleep duration was associated with a decrease of 2.07 cm² in VFA (regression coefficient = -2.07; 95% CI = -3.25 to -0.88), 2.67 cm² in SFA (-2.67; -4.55 to -0.78); 0.82 kg in bodyweight (-0.82; -1.2 to -0.43), 0.2 kg/m² in BMI (-0.2; -0.31 to -0.09) and 0.46 cm in WC (-0.46; -0.76 to -0.16). In the adjusted models, the shorter nocturnal sleep duration was still found to be associated with higher VFA, SFA, bodyweight, BMI and WC (except SFA and WC in models where we further adjusted for health conditions).

CONCLUSION

The nocturnal sleep duration among people with T2DM in Ningbo, China is negatively associated with visceral and general obesity indicators (VFA, bodyweight and BMI). Thus, there is a need for appropriate interventions to address the issue of sleep deprivation.

Actigraphy in mechanically ventilated pediatric ICU patients: comparison to PSG and evaluation of behavioral circadian rhythmicity

Sleep disruption is common in pediatric intensive care unit (PICU) patients, but measuring sleep in this population is challenging. We aimed to evaluate the utility of actigraphy for estimating circadian rhythmicity in mechanically ventilated PICU patients and its accuracy for measuring sleep by comparing it to polysomnogram (PSG). We conducted a single-center prospective observational study of children 6 months - 17 years of age receiving mechanical ventilation and standard, protocolized sedation for acute respiratory failure, excluding children with acute or historical neurologic injury. We enrolled 16 children and monitored them with up to 14 days of actigraphy and 24 hours of simultaneous limited (10 channel) PSG. Daily actigraphy-based activity profiles demonstrated that patients had a high level of nighttime activity (30-41% of total activity), suggesting disrupted circadian activity cycles. Among n = 12 patients with sufficient actigraphy and PSG data overlap, actigraphy-based sleep estimation showed poor agreement with PSG-identified sleep states, with good sensitivity (94%) but poor specificity (28%), low accuracy (70%,) and low agreement (Cohen's kappa = 0.2, 95% CI = 0.08-0.31). Using univariate linear regression, we identified that Cornell Assessment of Pediatric Delirium scores were associated with accuracy of actigraphy but that other clinical factors including sedative medication doses, activity levels, and restraint use were not. In this population, actigraphy did not reliably discern between sleep and wake states. However, in select patients, actigraphy was able to distinguish diurnal variation in activity patterns, and therefore may be useful for evaluating patients' response to circadian-oriented interventions.

Intermittent Fasting and Sleep: A Review of Human Trials

This review examines the effects of two popular intermittent fasting regimens on sleep in adults with overweight and obesity. Specifically, the effects of time restricted eating (TRE; eating all food within a 4-10 h window) and alternate day fasting (ADF; 600 kcal fast day alternated with ad libitum feast day) on sleep quality, sleep duration, sleep latency, sleep efficiency, insomnia severity, and risk of obstructive sleep apnea, will be summarized. The role of weight loss will also be discussed. Results from our review reveal that the majority of these trials produced weight loss in the range of 1-6% from baseline. Sleep quality and sleep duration remained unaltered with TRE and ADF, as assessed by the Pittsburgh Sleep Quality Index (PSQI). The effects of intermittent fasting on sleep latency and sleep efficiency are mixed, with one study showing worsening of these parameters, and others showing no effect. Insomnia severity and the risk of obstructive sleep apnea remained unchanged in the trials assessing these metrics. Taken together, these preliminary findings suggest that TRE and ADF produce mild to moderate weight loss (1-6%) but their effects on sleep remain unclear. Solid conclusions are difficult to establish since participants in the studies had healthy sleep durations and no clinical insomnia at baseline, leaving little room for improvement in these metrics. Moreover, none of the trials were adequately powered to detect statistically significant changes in any measure of sleep. Future well-powered trials, conducted in individuals with diagnosed sleep disturbances, will be necessary to elucidate the effect of these popular diets on sleep.

A Systematic Review of Sensing Technologies for Wearable Sleep Staging

Designing wearable systems for sleep detection and staging is extremely challenging due to the numerous constraints associated with sensing, usability, accuracy, and regulatory requirements. Several researchers have explored the use of signals from a subset of sensors that are used in polysomnography (PSG), whereas others have demonstrated the feasibility of using alternative sensing modalities. In this paper, a systematic review of the different sensing modalities that have been used for wearable sleep staging is presented. Based on a review of 90 papers, 13 different sensing modalities are identified. Each sensing modality is explored to identify signals that can be obtained from it, the sleep stages that can be reliably identified, the classification accuracy of systems and methods using the sensing modality, as well as the usability constraints of the sensor in a wearable system. It concludes that the two most common sensing modalities in use are those based on electroencephalography (EEG) and photoplethysmography (PPG). EEG-based systems are the most accurate, with EEG being the only sensing modality capable of identifying all the stages of sleep. PPG-based systems are much simpler to use and better suited for wearable monitoring but are unable to identify all the sleep stages.