Login / Signup

Comparing the activPAL software's Primary Time in Bed Algorithm against Self-Report and van der Berg's Algorithm.

J B CourtneyK NussK LydenK K HarrallD H GlueckA VillalobosR F HammanJ R HebertT G HurleyJ LeifermanK LiK AlaimoJ S Litt
Published in: Measurement in physical education and exercise science (2020)
The purpose of this study was to compare activPAL algorithm-estimated values for time in bed (TIB), wake time (WT) and bedtime (BT) against self-report and an algorithm developed by van der Berg and colleagues. Secondary analyses of baseline data from the Community Activity for Prevention Study (CAPS) were used in which adults ≥ 18 years wore the activPAL for seven days. Mixed-effects models compared differences between TIB, WT, and BT for all three methods. Bland-Altman plots examined agreement and the two-one-sided test examined equivalence. activPAL was not equivalent to self-report or van der Berg in estimating TIB, but was equivalent to self-report for estimating BT, and was equivalent to van der Berg for estimating WT. The activPAL algorithm requires adjustments before researchers can use it to estimate TIB. However, researchers can use activPAL's option to manually enter self-reported BT and WT to estimate TIB and better understand 24-hour movement patterns.
Keyphrases
  • machine learning
  • deep learning
  • neural network
  • healthcare
  • blood pressure
  • big data