Identifying bedrest using waist-worn triaxial accelerometers in preschool children

• Published in: PloS one 2021-01, Vol.16 (1), p.e0246055-e0246055
• Main Authors: Tracy, J Dustin, Donnelly, Thomas, Sommer, Evan C, Heerman, William J, Barkin, Shari L, Buchowski, Maciej S
• Format: Article
• Language: English
• Subjects: Abnormalities; Accelerometers; Algorithms; Automation; Biology and Life Sciences; Body mass index; Body weight; Children; Children & youth; Computer programs; Data collection; Decision tree; Drafting software; Editing; Energy balance; Engineering and Technology; Exercise; Funding; Gastroenterology; Health aspects; Health care facilities; Hepatology; Identification; Identification and classification; Laboratories; Medicine; Medicine and Health Sciences; Methodology; Nutrition; Pediatric research; Pediatrics; Physical activity; Physical Sciences; Preschool children; Research and Analysis Methods; Reviews; Sleep; Software
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0246055

To adapt and validate a previously developed decision tree for youth to identify bedrest for use in preschool children. Parents of healthy preschool (3-6-year-old) children (n = 610; 294 males) were asked to help them to wear an accelerometer for 7 to 10 days and 24 hours/day on their waist. Children with ≥3 nights of valid recordings were randomly allocated to the development (n = 200) and validation (n = 200) groups. Wear periods from accelerometer recordings were identified minute-by-minute as bedrest or wake using visual identification by two independent raters. To automate visual identification, chosen decision tree (DT) parameters (block length, threshold, bedrest-start trigger, and bedrest-end trigger) were optimized in the development group using a Nelder-Mead simplex optimization method, which maximized the accuracy of DT-identified bedrest in 1-min epochs against synchronized visually identified bedrest (n = 4,730,734). DT's performance with optimized parameters was compared with the visual identification, commonly used Sadeh's sleep detection algorithm, DT for youth (10-18-years-old), and parental survey of sleep duration in the validation group. On average, children wore an accelerometer for 8.3 days and 20.8 hours/day. Comparing the DT-identified bedrest with visual identification in the validation group yielded sensitivity = 0.941, specificity = 0.974, and accuracy = 0.956. The optimal block length was 36 min, the threshold 230 counts/min, the bedrest-start trigger 305 counts/min, and the bedrest-end trigger 1,129 counts/min. In the validation group, DT identified bedrest with greater accuracy than Sadeh's algorithm (0.956 and 0.902) and DT for youth (0.956 and 0.861) (both P