ArticleNature and science of sleep2022
Actigraphy-Based Sleep Detection: Validation with Polysomnography and Comparison of Performance for Nighttime and Daytime Sleep During Simulated Shift Work.
Article in Nature and science of sleep, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 27 citations in OpenAlex.
- Effect of a multimodal exercise training program on sleep in older adults: a randomized controlled trial.Brazilian journal of physical therapyTrial
- Article
- Cross-sectional associations between actigraphy-measured sleep and 24-h ambulatory blood pressure phenotypes among self-reported short sleepers with elevated blood pressure.Sleep medicine · 2026Article
- Objectively Measured Daytime Napping Patterns and All-Cause Mortality in Older Adults.JAMA network open · 2026Article
- Longitudinal association between sleep and Alzheimer's pathology.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Article
- Apnea-hypopnea index estimation using overnight chest-wall accelerometry.Frontiers in sleep · 2026Article
- Comparison and Validation of Actigraphy Algorithms Using a Large Community Dataset: Algorithm Validation Study.JMIR formative research · 2025Article
- Performance evaluation of an under-mattress sleep sensor versus polysomnography in > 400 nights with healthy and unhealthy sleep.Journal of sleep research · 2025Article
- Beyond the Sleep Lab: A Narrative Review of Wearable Sleep Monitoring.Bioengineering (Basel, Switzerland) · 2025Review
- Actigraphy-derived sleep fragmentation index: convergent validity and associations with clinical outcomes.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach.Journal of medical Internet research · 2025Article
- Timing and intraindividual variability of daytime napping and Alzheimer's disease in older adults.Communications medicine · 2025Article
- Cognitive behavioural therapy for insomnia decreases the discrepancy between objective and subjective measures of sleep.Trends in psychiatry and psychotherapy · 2025Article
- Article
- Overnight Sleep Staging Using Chest-Worn Accelerometry.Sensors (Basel, Switzerland) · 2024Article
- Actigraphy-based sleep and muscle sympathetic nerve activity in humans.American journal of physiology. Regulatory, integrative and comparative physiology · 2024Article
- Article
- Article
- Effects of sleep on breakfast behaviors in recently unemployed adults.Sleep health · 2024Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Purpose: Actigraphy-based sleep detection algorithms were mostly validated using nighttime sleep, and their performance in detecting daytime sleep is unclear. We evaluated and compared the performance of Actiware and the Cole-Kripke algorithm (C-K) - two commonly used actigraphy-based algorithms - in detecting daytime and nighttime sleep. Participants and Methods: Twenty-five healthy young adults were monitored by polysomnography and actigraphy during two in-lab protocols with scheduled nighttime and/or daytime sleep (within-subject design). Mixed-effect models were conducted to compare the sensitivity, specificity, and F1 score (a less-biased measure of accuracy) of Actiware (with low/medium/high threshold setting, separately) and C-K in detecting sleep epochs from actigraphy recordings during nighttime/daytime. Results: Sensitivity was similar between nighttime (Actiware: 0.93-0.99 across threshold settings; C-K: 0.61) and daytime sleep (Actiware: 0.93-0.99; C-K: 0.66) for both the C-K and Actiware (daytime/nighttime×algorithm interaction: p > 0.1). Specificity for daytime sleep was lower (Actiware: 0.35-0.54; C-K: 0.91) than that for nighttime sleep (Actiware: 0.37-0.62; C-K: 0.93; p = 0.001). Specificity was also higher for C-K than Actiware (p < 0.001), with no daytime/nighttime×algorithm interaction (p > 0.1). C-K had lower F1 (nighttime = 0.74; daytime = 0.77) than Actiware (nighttime = 0.95-0.98; daytime = 0.90-0.91) for both nighttime and daytime sleep (all p < 0.05). The daytime-nighttime difference in F1 was opposite for Actiware (daytime: 0.90-0.91; nighttime: 0.95-0.98) and C-K (daytime: 0.77; nighttime: 0.74; interaction p = 0.003). Bias in TST was lowest in Actiware (with medium-threshold) for nighttime sleep (underestimation of 5.99 min/8h) and in Actiware (with low-threshold) for daytime sleep (overestimation of 17.75 min/8h). Conclusion: Daytime/nighttime sleep affected specificity and F1 but not sensitivity of actigraphy-based sleep scoring. Overall, Actiware performed better than the C-K algorithm. Actiware with medium-threshold was the least biased in estimating nighttime TST, and Actiware with low-threshold was the least biased in estimating daytime TST.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.