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Journal of Sleep Research Jun 2021Actigraphy is a cost-efficient method to estimate sleep-wake patterns over long periods in natural settings. However, the lack of methodological standards in actigraphy... (Review)
Review
Actigraphy is a cost-efficient method to estimate sleep-wake patterns over long periods in natural settings. However, the lack of methodological standards in actigraphy research complicates the generalization of outcomes. A rapidly growing methodological diversity is visible in the field, which increasingly necessitates the detailed reporting of methodology. We address this problem and evaluate the current state of the art and recent methodological developments in actigraphy reporting with a special focus on infants and young children. Through a systematic literature search on PubMed (keywords: sleep, actigraphy, child *, preschool, children, infant), we identified 126 recent articles (published since 2012), which were classified and evaluated for reporting of actigraphy. Results show that all studies report on the number of days/nights the actigraph was worn. Reporting was good with respect to device model, placement and sleep diary, whereas reporting was worse for epoch length, algorithm, artefact identification, data loss and definition of variables. In the studies with infants only (n = 58), the majority of articles (62.1%) reported a recording of actigraphy that was continuous across 24 hr. Of these, 23 articles (63.9%) analysed the continuous 24-hr data and merely a fifth used actigraphy to quantify daytime sleep. In comparison with an evaluation in 2012, we observed small improvements in reporting of actigraphy methodology. We propose stricter adherence to standards in reporting methodology in order to streamline actigraphy research with infants and young children, to improve comparability and to facilitate big data ventures in the sleep community.
Topics: Accelerometry; Actigraphy; Female; Humans; Male; Research Design; Sleep
PubMed: 32638500
DOI: 10.1111/jsr.13134 -
Journal of Sleep Research Aug 2019Actigraphy is increasingly used in practice and research studies because of its relative low cost and decreased subject burden. How multiple nights of at-home actigraphy...
Actigraphy is increasingly used in practice and research studies because of its relative low cost and decreased subject burden. How multiple nights of at-home actigraphy compare to one independent night of in-laboratory polysomnography (PSG) has not been examined in people with insomnia. Using event markers (MARK) to set time in bed (TIB) compared to automatic program analysis (AUTO) has not been systematically evaluated. Subjects (n = 30) meeting DSM-5 criteria for insomnia and in-laboratory PSG sleep efficiency (SE) of <85% were studied. Subjects were free of psychiatric, sleep or circadian disorders, other chronic conditions and medications that effect sleep. Subjects had an in-laboratory PSG, then were sent home for 7 nights with Philips Actiwatch Spectrum Plus. Data were analysed using Philips Actiware version 6. Using the mean of seven nights, TIB, total sleep time (TST), SE, sleep-onset latency (SOL) and wake after sleep onset (WASO) were examined. Compared to PSG, AUTO showed longer TIB and TST and less WASO. MARK only differed from PSG with decreased WASO. Differences between the PSG night and the following night at home were found, with better sleep on the first night home. Actigraphy in people with insomnia over seven nights is a valid indicator of sleep compared to an independent in-laboratory PSG. Event markers increased the validity of actigraphy, showing no difference in TIB, TST, SE and SOL. AUTO was representative of SE and SOL. Increased SE and TST without increased TIB suggests possible compensatory sleep the first at night home after in-laboratory PSG.
Topics: Actigraphy; Female; Humans; Male; Middle Aged; Polysomnography; Sleep Initiation and Maintenance Disorders
PubMed: 30941838
DOI: 10.1111/jsr.12854 -
Annals of Work Exposures and Health Apr 2020Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies...
Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies because of its ability to monitor activity in natural settings. Using special software, actigraphic data are analyzed to estimate a range of sleep parameters. To date, despite extensive application of actigraphs in sleep research, published literature specifically detailing the methodology for derivation of sleep parameters is lacking; such information is critical for the appropriate analysis and interpretation of actigraphy data. Reporting of sleep parameters has also been inconsistent across studies, likely reflecting the lack of consensus regarding the definition of sleep onset and offset. In addition, actigraphy data are generally underutilized, with only a fraction of the sleep parameters generated through actigraphy routinely used in current sleep research. The objectives of this paper are to review existing algorithms used to estimate sleep/wake cycles from movement data, demonstrate the rules/methods used for estimating sleep parameters, provide clear technical definitions of the parameters, and suggest potential new measures that reflect intraindividual variability. Utilizing original data collected using Motionlogger Sleep Watch (Ambulatory Monitoring Inc., Ardsley, NY), we detail the methodology and derivation of 29 nocturnal sleep parameters, including those both widely and rarely utilized in research. By improving understanding of the actigraphy process, the information provided in this paper may help: ensure appropriate use and interpretation of sleep parameters in future studies; enable the recalibration of sleep parameters to address specific goals; inform the development of new measures; and increase the breadth of sleep parameters used.
Topics: Actigraphy; Algorithms; Humans; Sleep; Software
PubMed: 32053169
DOI: 10.1093/annweh/wxaa007 -
Journal of Sleep Research Aug 2022The identification of optimal sleep duration recommendations for the general population has long been an important goal on the public health agenda, as both short and... (Review)
Review
The identification of optimal sleep duration recommendations for the general population has long been an important goal on the public health agenda, as both short and long sleep duration have been linked to unfavourable health outcomes. Yet, sleep is more than duration alone and can be described across multiple domains, such as timing, regularity, satisfaction, alertness, and efficiency. We reviewed observational population-based studies that examined differences in age, sex, and origin across multiple dimensions of sleep. Reviewed literature suggests an increasing prevalence of insomnia symptoms, shorter and less deep sleep in old age. Overall, women report poorer sleep quality than men despite objective measures revealing shorter and more fragmented sleep in men. Minorities generally have poorer quantity and quality of sleep, but multi-ethnic studies have reported mixed results regarding the subjective experience of sleep. In sum, effects of age, sex and origin differ across sleep dimensions, thereby suggesting that the multidimensionality of sleep and how these different aspects interact should be studied across individuals. Studies should include both self-reported measures and objective assessments in diverse population-based samples, as both aspects are important to understand sleep health in the general population. Data-driven descriptions could provide researchers and clinicians with insights into how well individuals are sleeping and offer concrete targets for promotion of sleep health across the population.
Topics: Actigraphy; Ethnicity; Female; Humans; Male; Self Report; Sleep; Sleep Initiation and Maintenance Disorders
PubMed: 35429087
DOI: 10.1111/jsr.13608 -
Scientific Reports Mar 2022We explored the associations of actigraphy-derived rest-activity patterns and circadian phase parameters with clinical symptoms and level 1 polysomnography (PSG) results...
We explored the associations of actigraphy-derived rest-activity patterns and circadian phase parameters with clinical symptoms and level 1 polysomnography (PSG) results in patients with chronic insomnia to evaluate the clinical implications of actigraphy-derived parameters for PSG interpretation. Seventy-five participants underwent actigraphy assessments and level 1 PSG. Exploratory correlation analyses between parameters derived from actigraphy, PSG, and clinical assessments were performed. First, participants were classified into two groups based on rest-activity pattern variables; group differences were investigated following covariate adjustment. Participants with poorer rest-activity patterns on actigraphy (low inter-day stability and high intra-daily variability) exhibited higher insomnia severity index scores than participants with better rest-activity patterns. No between-group differences in PSG parameters were observed. Second, participants were classified into two groups based on circadian phase variables. Late-phase participants (least active 5-h and most active 10-h onset times) exhibited higher insomnia severity scores, longer sleep and rapid eye movement latency, and lower apnea-hypopnea index than early-phase participants. These associations remained significant even after adjusting for potential covariates. Some actigraphy-derived rest-activity patterns and circadian phase parameters were significantly associated with clinical symptoms and PSG results, suggesting their possible adjunctive role in deriving plans for PSG lights-off time and assessing the possible insomnia pathophysiology.
Topics: Actigraphy; Humans; Polysomnography; Sleep; Sleep Initiation and Maintenance Disorders; Sleep, REM
PubMed: 35318367
DOI: 10.1038/s41598-022-08899-2 -
Sleep Medicine Reviews Feb 2018Sleep disturbances are the main health complaints from personnel deployed in Antarctica. The current paper presents a systematic review of research findings on sleep... (Review)
Review
Sleep disturbances are the main health complaints from personnel deployed in Antarctica. The current paper presents a systematic review of research findings on sleep disturbances in Antarctica. The available sources were divided in three categories: results based on questionnaire surveys or sleep logs, studies using actigraphy, and data from polysomnography results. Other areas relevant to the issue were also examined. These included chronobiology, since the changes in photoperiod have been known to affect circadian rhythms, mood disturbances, exercise, sleep and hypoxia, countermeasure investigations in Antarctica, and other locations lacking a normal photoperiod. Based on the combination of our reviewed sources and data outside the field of sleep studies, or from other geographical locations, we defined hypotheses to be confirmed or infirmed, which allowed to summarize a research agenda. Despite the scarcity of sleep research on the Antarctic continent, the present review pinpointed some consistent changes in sleep during the Antarctic winter, the common denominators being a circadian phase delay, poor subjective sleep quality, an increased sleep fragmentation, as well as a decrease in slow wave sleep. Similar changes, albeit less pronounced, were observed during summer. Additional multidisciplinary research is needed to elucidate the mechanisms behind these changes in sleep architecture, and to investigate interventions to improve the sleep quality of the men and women deployed in the Antarctic.
Topics: Actigraphy; Adaptation, Psychological; Antarctic Regions; Circadian Rhythm; Humans; Photoperiod; Polysomnography; Seasons; Sleep; Sleep Initiation and Maintenance Disorders; Surveys and Questionnaires
PubMed: 28460798
DOI: 10.1016/j.smrv.2017.03.001 -
Psychosomatic Medicine May 2022Sleep changes over the human life span, and it does so across multiple dimensions. We used individual-level cross-sectional data to characterize age trends and sex...
OBJECTIVE
Sleep changes over the human life span, and it does so across multiple dimensions. We used individual-level cross-sectional data to characterize age trends and sex differences in actigraphy and self-report sleep dimensions across the healthy human life span.
METHODS
The Pittsburgh Lifespan Sleep Databank consists of harmonized participant-level data from sleep-related studies conducted at the University of Pittsburgh (2003-2019). We included data from 1065 (n = 577 female; 21 studies) Pittsburgh Lifespan Sleep Databank participants aged 10 to 87 years without a major psychiatric, sleep, or medical condition. All participants completed wrist actigraphy and the self-rated Pittsburgh Sleep Quality Index. Main outcomes included actigraphy and self-report sleep duration, efficiency, and onset/offset timing, and actigraphy variability in midsleep timing.
RESULTS
We used generalized additive models to examine potentially nonlinear relationships between age and sleep characteristics and to examine sex differences. Actigraphy and self-report sleep onset time shifted later between ages 10 and 18 years (23:03-24:10 [actigraphy]; 21:58-23:53 [self-report]) and then earlier during the 20s (00:08-23:40 [actigraphy]; 23:50-23:34 [self-report]). Actigraphy and self-report wake-up time also shifted earlier during the mid-20s through late 30s (07:48-06:52 [actigraphy]; 07:40-06:41 [self-report]). Self-report, but not actigraphy, sleep duration declined between ages 10 and 20 years (09:09-07:35). Self-report sleep efficiency decreased over the entire life span (96.12-93.28), as did actigraphy variability (01:54-01:31).
CONCLUSIONS
Awareness of age trends in multiple sleep dimensions in healthy individuals-and explicating the timing and nature of sex differences in age-related change-can suggest periods of sleep-related risk or resilience and guide intervention efforts.
Topics: Actigraphy; Cross-Sectional Studies; Female; Humans; Longevity; Male; Self Report; Sleep
PubMed: 35100181
DOI: 10.1097/PSY.0000000000001060 -
Journal of Sleep Research Dec 2022This work aimed to evaluate if a contact-free radar sensor can be used to observe ultradian patterns in sleep physiology, by way of a data processing tool known as...
This work aimed to evaluate if a contact-free radar sensor can be used to observe ultradian patterns in sleep physiology, by way of a data processing tool known as Locomotor Inactivity During Sleep (LIDS). LIDS was designed as a simple transformation of actigraphy recordings of wrist movement, meant to emphasise and enhance the contrast between movement and non-movement and to reveal patterns of low residual activity during sleep that correlate with ultradian REM/NREM cycles. We adapted the LIDS transformation for a radar that detects body movements without direct contact with the subject and applied it to a dataset of simultaneous recordings with polysomnography, actigraphy, and radar from healthy young adults (n = 12, four nights of polysomnography per participant). Radar and actigraphy-derived LIDS signals were highly correlated with each other (r > 0.84), and the LIDS signals were highly correlated with reduced-resolution polysomnographic hypnograms (r >0.80, r >0.76). Single-harmonic cosine models were fitted to LIDS signals and hypnograms; significant differences were not found between their amplitude, period, and phase parameters. Mixed model analysis revealed similar slopes of decline per cycle for radar-LIDS, actigraphy-LIDS, and hypnograms. Our results indicate that the LIDS technique can be adapted to work with contact-free radar measurements of body movement; it may also be generalisable to data from other body movement sensors. This novel metric could aid in improving sleep monitoring in clinical and real-life settings, by providing a simple and transparent way to study ultradian dynamics of sleep using nothing more than easily obtainable movement data.
Topics: Young Adult; Humans; Radar; Sleep; Polysomnography; Actigraphy; Movement
PubMed: 35794011
DOI: 10.1111/jsr.13687 -
Sensors (Basel, Switzerland) 2012Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a... (Review)
Review
Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications.
Topics: Acceleration; Actigraphy; Algorithms; Clothing; Gait; Humans; Monitoring, Ambulatory; Transducers
PubMed: 22438763
DOI: 10.3390/s120202255 -
Annals of Medicine Dec 2023Discriminating sleep period from accelerometer data remains a challenge despite many studies have adapted 24-h measurement protocols. We aimed to compare and examine the...
OBJECTIVES
Discriminating sleep period from accelerometer data remains a challenge despite many studies have adapted 24-h measurement protocols. We aimed to compare and examine the agreement among device-estimated and self-reported bedtime, wake-up time, and sleep periods in a sample of adults.
MATERIALS AND METHODS
Participants (108 adults, 61 females) with an average age of 33.1 (SD 0.4) were asked to wear two wearable devices (Polar Active and Ōura ring) simultaneously and record their bedtime and wake up time using a sleep diary. Sleep periods from Polar Active were detected using an in-lab algorithm, which is openly available. Sleep periods from Ōura ring were generated by commercial Ōura system. Scatter plots, Bland-Altman plots, and intraclass correlation coefficients (ICCs) were used to evaluate the agreement between the methods.
RESULTS
Intraclass correlation coefficient values were above 0.81 for bedtimes and wake-up times between the three methods. In the estimation of sleep period, ICCs ranged from 0.67 (Polar Active vs. sleep diary) to 0.76 (Polar Active vs. Ōura ring). Average difference between Polar Active and Ōura ring was -1.8 min for bedtimes and -2.6 min for wake-up times. Corresponding values between Polar Active and sleep diary were -5.4 and -18.9 min, and between Ōura ring and sleep diary -3.6 min and -16.2 min, respectively.
CONCLUSION
Results showed a high agreement between Polar Active activity monitor and Ōura ring for sleep period estimation. There was a moderate agreement between self-report and the two devices in estimating bedtime and wake-up time. These findings suggest that potentially wearable devices can be interchangeably used to detect sleep period, but their accuracy remains limited.Key MessagesEstimation of sleep period from different devices could be comparable.Difference between sleep periods from monitors and sleep diary are under 20 min.Device-based estimation of sleep period is encouraged in population-based studies.
Topics: Female; Humans; Adult; Self Report; Sleep; Caffeine; Actigraphy
PubMed: 37086052
DOI: 10.1080/07853890.2023.2191001