ArticlePhysiological measurement2019
Parameterizing and validating existing algorithms for identifying out-of-bed time using hip-worn accelerometer data from older women.
Article in Physiological measurement, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Cleaning and pre-processing of actigraphy data for physical activity and sleep research: a scoping review.Physiological measurement · 2026Article
- Accelerometer-Measured Daily Steps, Physical Function, and Subsequent Fall Risk in Older Women: The Objective Physical Activity and Cardiovascular Disease in Older Women Study.Journal of aging and physical activity · 2022Article
- Associations of Daily Steps and Step Intensity With Incident Diabetes in a Prospective Cohort Study of Older Women: The OPACH Study.Diabetes care · 2022Article
- Simple Method for the Objective Activity Type Assessment with Preschoolers, Children and Adolescents.Children (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectiveTo parameterize and validate two existing algorithms for identifying out-of-bed time using 24 h hip-worn accelerometer data from older women. APPROACH: Overall, 628 women (80 ± 6 years old) wore ActiGraph GT3X+ accelerometers 24 h d MAIN
resultsWaking wear time agreement with the criterion was high for Tracy_ SIGNIFICANCE: The McVeigh algorithm with optimal parameters using VM performed best compared to criterion sleep-log assisted visual analysis and is suitable for automated identification of waking wear time in older women when visual analysis is not feasible.
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