Sleep Measurement Using Wrist-Worn Accelerometer Data Compared with Polysomnography

Chase, John D.; Staudenmayer, John; Sirard, John R.

doi:10.3390/s22135041

Cited by 17 publications

(14 citation statements)

References 54 publications

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“…Actigraphy has limitations in providing detailed information about the athletes’ sleep, and it is important to note that it may have certain flaws, such as underestimating sleep latency and overestimating sleep efficiency, which could lead to measurement inaccuracies. 13 …”

Section: Discussionmentioning

confidence: 99%

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Sleep Patterns During Pre-Competition Training Phase: A Comparison Between Male and Female Collegiate Swimmers

Xu,

2024

NSS

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While there is a rising focus on sleep issues among athletes, a notable gap exists in the comparative analysis of sleep patterns between male and female athletes. This study aims to evaluate the sleep patterns of collegiate swimmers during a specific period (pre-competition training phase) based on the National Sleep Foundation's recommendations and compares sleep differences between males and females. Patients and Methods: 15 swimmers (6 males and 9 females) completed the Athlete Sleep Screening Questionnaire (ASSQ) and wore actigraphy devices for 8 consecutive nights to record objective sleep patterns including bedtime, wake time, sleep onset latency, total sleep time, wake after sleep onset, and sleep efficiency. Results: The total sleep time of collegiate male (5.0±0.4 h, 4.6 to 5.4h) and female (6.0±0.7 h, 5.5 to 6.5h) swimmers was less than 7 hours per night, and male swimmers' sleep efficiency (76.7±8.9%, 67.4 to 86.0%) was lower than the 85% standard. Male swimmers had less objectively measured sleep duration (p=0.006, d=1.66, large effect), lower sleep efficiency (p=0.013, d=1.51, large effect), and longer wake after sleep onset (p=0.096, d=0.94, moderate effect). Female swimmers had higher sleep difficulty scores (p=0.06, d=1.08, moderate effect), and there was a significant difference in the distribution of sleep difficulty scores between male and female swimmers (p=0.033, V=0.045, small effect). Conclusion:Collegiate swimmers exhibited poor sleep patterns during pre-competition preparation, and the sleep fragmentation of male swimmers was more pronounced. There were sex differences in both subjective and objective measured sleep patterns, with male swimmers having less sleep and low efficiency, while female swimmers experienced more significant sleep disturbances.

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Section: Discussionmentioning

confidence: 99%

“…Compared to Polysomnography (PSG), GT3x exhibits 90% sensitivity and 84% accuracy. 13 Participants were instructed to wear the actigraphy devices throughout the day, except when swimming or bathing. The actigraphy devices were set to a sampling rate of 30 Hz and a 1-minute epoch for activity counts.…”

Section: Sleep Assessment Objective Sleep Measurementmentioning

confidence: 99%

Sleep Patterns During Pre-Competition Training Phase: A Comparison Between Male and Female Collegiate Swimmers

Xu,

2024

NSS

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“…An ActiGraph GT3X + accelerometer (ActiGraph, Illinois, USA) will be used to objectively monitor physical activity, sedentary behavior, and sleep time. The accelerometer has been validated for assessing physical activity, sedentary behavior, and sleep quality (32,33).…”

Section: Physical Activity Sedentary Time and Sleep Timementioning

confidence: 99%

“…We will use an ActiGraph accelerometer to measure sleep quality (32,33). This variable plays a fundamental role in cardiovascular health (48).…”

Section: Other Measurements (Covariates)mentioning

confidence: 99%

Study Protocol and Rationale of “The UP Project”: Evaluating the Effectiveness of Active Breaks on Health Indicators in Desk-Based Workers

Cristi-Montero,

Martínez-Flores,

Espinoza-Puelles

et al. 2023

Preprint

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BackgroundExcessive sedentary time has been negatively associated with several health outcomes, and physical activity alone does not seem to fully counteract these consequences. This panorama emphasizes the essential of sedentary time interruption programs. “The Up Project” seeks to assess the effectiveness of two interventions, one incorporating active breaks led by a professional and the other utilizing a computer application (self-led), of both equivalent duration and intensity. These interventions will be compared with a control group to evaluate their impact on physical activity levels, sedentary time, stress perception, occupational pain, and cardiometabolic risk factors among office workers.MethodsThis quasi-experimental study includes 60 desk-based workers from universities and educational institutes in Valparaiso, Chile, assigned to three groups: a) booster breaks led by professionals, b) computer prompts that are unled, and c) a control group. The intervention protocol for both experimental groups will last 12 weeks (only weekdays). The following measurements will be performed at baseline and post-intervention: cardiometabolic risk based on body composition (fat mass, fat-free mass, and bone mass evaluated by DXA), waist circumference, blood pressure, and resting heart rate. Physical activity and sedentary time will be self-reported and objectively assessed using accelerometry. Questionnaires will be used to determine the perception of stress and occupational pain.DiscussionGovernments worldwide are addressing health issues associated with sedentary behavior, particularly concerning individuals highly exposed to it, such as desk-based workers. Despite implementing certain strategies, there remains a noticeable gap in comprehensive research comparing diverse protocols. For instance, studies that contrast the outcomes of interventions led by professionals with those prompted by computers are scarce. This ongoing project is expected to contribute to evidence-based interventions targeting reduced perceived stress levels and enhancing desk-based employees’ mental and physical well-being. The implications of these findings could have the capacity to lay the groundwork for future public health initiatives and government-funded.

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“…Due to the body movement variations specific to each sleep stage, accelerometers can provide information about wakefulness and general sleep stages. However, they may tend to overestimate sleep due to poorly distinguishing between sleep and sedentary supine wake periods (eg, lying down while reading or watching television), or they could underestimate sleep due to potential body movements during sleep being categorized as awakenings [ 12 15-18 undefined undefined undefined ]. In addition, they may not be as accurate in distinguishing between different non–rapid eye movement (REM) stages and detecting subtle changes in sleep architecture [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review

Schyvens,

Van Oost,

Aerts

et al. 2024

JMIR Mhealth Uhealth

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Background Despite being the gold-standard method for objectively assessing sleep, polysomnography (PSG) faces several limitations as it is expensive, time-consuming, and labor-intensive; requires various equipment and technical expertise; and is impractical for long-term or in-home use. Consumer wrist-worn wearables are able to monitor sleep parameters and thus could be used as an alternative for PSG. Consequently, wearables gained immense popularity over the past few years, but their accuracy has been a major concern. Objective A systematic review of the literature was conducted to appraise the performance of 3 recent-generation wearable devices (Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP) in determining sleep parameters and sleep stages. Methods Per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, a comprehensive search was conducted using the PubMed, Web of Science, Google Scholar, Scopus, and Embase databases. Eligible publications were those that (1) involved the validity of sleep data of any marketed model of the candidate wearables and (2) used PSG or an ambulatory electroencephalogram monitor as a reference sleep monitoring device. Exclusion criteria were as follows: (1) incorporated a sleep diary or survey method as a reference, (2) review paper, (3) children as participants, and (4) duplicate publication of the same data and findings. Results The search yielded 504 candidate articles. After eliminating duplicates and applying the eligibility criteria, 8 articles were included. WHOOP showed the least disagreement relative to PSG and Sleep Profiler for total sleep time (−1.4 min), light sleep (−9.6 min), and deep sleep (−9.3 min) but showed the largest disagreement for rapid eye movement (REM) sleep (21.0 min). Fitbit Charge 4 and Garmin Vivosmart 4 both showed moderate accuracy in assessing sleep stages and total sleep time compared to PSG. Fitbit Charge 4 showed the least disagreement for REM sleep (4.0 min) relative to PSG. Additionally, Fitbit Charge 4 showed higher sensitivities to deep sleep (75%) and REM sleep (86.5%) compared to Garmin Vivosmart 4 and WHOOP. Conclusions The findings of this systematic literature review indicate that the devices with higher relative agreement and sensitivities to multistate sleep (ie, Fitbit Charge 4 and WHOOP) seem appropriate for deriving suitable estimates of sleep parameters. However, analyses regarding the multistate categorization of sleep indicate that all devices can benefit from further improvement in the assessment of specific sleep stages. Although providers are continuously developing new versions and variants of wearables, the scientific research on these wearables remains considerably limited. This scarcity in literature not only reduces our ability to draw definitive conclusions but also highlights the need for more targeted research in this domain. Additionally, future research endeavors should strive for standardized protocols including larger sample sizes to enhance the comparability and power of the results across studies.

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Sleep Measurement Using Wrist-Worn Accelerometer Data Compared with Polysomnography

Cited by 17 publications

References 54 publications

Sleep Patterns During Pre-Competition Training Phase: A Comparison Between Male and Female Collegiate Swimmers

Sleep Patterns During Pre-Competition Training Phase: A Comparison Between Male and Female Collegiate Swimmers

Study Protocol and Rationale of “The UP Project”: Evaluating the Effectiveness of Active Breaks on Health Indicators in Desk-Based Workers

Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review

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