This paper is in the following e-collection/theme issue:

Theme Issue 2024: 25 Years of Digital Health Excellence (44) Digital Health Reviews (1469) Fitness Trackers and Smart Pedometers/Accelerometers (603) Wearable Devices and Sensors (975) Evaluation and Research Methodology for mHealth (219) Instruments and Questionnaires for Physical Activity and Lifestyle (89)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59497, first published .
Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review

Authors of this article:

Ya-Ting Liang1, 2 Author Orcid Image ;   Charlotte Wang2, 3 Author Orcid Image ;   Chuhsing Kate Hsiao2, 3 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Graham B, Farrell M. Mortality prediction using data from wearable activity trackers and individual characteristics: An explainable artificial intelligence approach. Expert Systems with Applications 2025;267:126195 View
  2. Liang Y, Wang C. Motif clustering and digital biomarker extraction for free-living physical activity analysis. BioData Mining 2025;18(1) View
  3. Machado-Rodrigues A, Rodrigues D, Nogueira H, Gama A, Fernandes H, Neto A, Padez C. The Risk of Pediatric Overweight and Children’s Objectively Measured Sedentary Behaviors and Physical Activity by Area of Residence. Healthcare 2025;13(5):462 View
  4. Machado-Rodrigues A, Rodrigues D, da Silva T, Mendes L, Silva P, Nogueira H, Gama A, Padez C. Variability in moderate-to-vigorous physical activity assessment: Comparing tri-axial accelerometry cut-off points in children. Sports Medicine and Health Science 2025 View