Document Type
Article
Publication Date
4-24-2019
Abstract
Objective: To parameterize and validate two existing algorithms for identifying out-of-bed time using 24-hour hip-worn accelerometer data from older women. Approach: Overall, 628 women (80±6 years old) wore ActiGraph GT3X+ accelerometers 24 hours/day for up to 7 days and concurrently completed sleep-logs. Trained staff used a validated visual analysis protocol to measure in-bed periods on accelerometer tracings (criterion). The Tracy and McVeigh algorithms were adapted for optimal use in older adults. A training set of 314 women was used to choose two key thresholds by maximizing the sum of sensitivity and specificity for each algorithm and data (vertical axis, VA, and vector magnitude, VM) combination. Data from the remaining 314 women were then used to test agreement in waking wear time (i.e., out-of-bed time while wearing the accelerometer) by computing sensitivity, specificity, and kappa comparing the algorithm output with the criterion. Waking wear time-adjusted means of sedentary time, light-intensity physical activity (light PA) and moderate-to-vigorous-intensity physical activity (MVPA) were then estimated and compared. Main results: Waking wear time agreement with the criterion was high for Tracy_VA, Tracy_VM, McVeigh_VA, and highest for McVeigh_VM. Compared to the criterion, McVeigh_VM had mean sensitivity=0.92, specificity=0.87, kappa=0.80, and overall mean difference (±SD) of -0.04±2.5 hours/day. Minutes of sedentary time, light PA, and MVPA adjusted for waking wear time using the criterion measure and McVeigh_VM were not statistically different (p >0.43 | all). 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.
Recommended Citation
Belletierre, J., Zhang, Y., Berardi, V., Full, K. M., Kerr, J., LaMonte, M. J., Evenson, K. R., Hovell, M., LaCroix, A. Z., & Di, C. (2019). Parameterizing and validating existing algorithms for identifying out-of-bed time using hip-worn accelerometer data from older women. Physiological Measurement, 40(7): 075008. https://doi.org/10.1088/1361-6579/ab1c04
Copyright
Institute of Physics and Engineering in Medicine
Included in
Equipment and Supplies Commons, Other Psychiatry and Psychology Commons, Psychological Phenomena and Processes Commons, Women's Health Commons
Comments
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Physiological Measurement, volume 40, issue 7 in 2019 following peer review. The definitive publisher-authenticated version will be available online at DOI: 10.1088/1361-6579/ab1c04.