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

Formative Evaluation of Digital Health Interventions (5381) Usability of Apps and User Perceptions of mHealth (1840) Registered Report (1581)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48209, first published .
MOTUS app on phone, showing login with phone number, with data charts on monitor.

A Novel System for the Device-Based Measurement of Physical Activity, Sedentary Behavior, and Sleep (Motus): Usability Evaluation

A Novel System for the Device-Based Measurement of Physical Activity, Sedentary Behavior, and Sleep (Motus): Usability Evaluation

Authors of this article:

Patrick Crowley1 Author Orcid Image ;   Rasmus Kildedal1 Author Orcid Image ;   Simon Overvad Vindelev1 Author Orcid Image ;   Sandra Schade Jacobsen1 Author Orcid Image ;   Jon Roslyng Larsen1 Author Orcid Image ;   Peter J Johansson2, 3 Author Orcid Image ;   Mette Aadahl4, 5 Author Orcid Image ;   Leon Straker6 Author Orcid Image ;   Emmanuel Stamatakis7, 8 Author Orcid Image ;   Andreas Holtermann1 Author Orcid Image ;   Paul Jarle Mork9 Author Orcid Image ;   Nidhi Gupta1 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Ludvigsen T, Hørlück S, Larsen J, Lund C, Hettiarachchi P, Brandt M, Gupta N. Validation and comparative study of the Motus system for accurately identifying movement behaviours using different sampling frequencies. Scientific Reports 2025;15(1) View
  2. Ahrensberg H, Christensen A, Andersen S, Petersen C. Comparison of self-reported sleep sufficiency and accelerometer-measured sleep duration in relation to mental health, physical health, and life satisfaction. Frontiers in Sleep 2025;4 View
  3. Gupta N, Eghøj M, Pedersen Ludvigsen T, Larsen J, Wester C, Kildedal R, Stamatakis E, Straker L, Aadahl M, Johansson P, Mork P, Petersen C, Holtermann A. A Feasibility Study of the “Motus” System for Wearable-Based Movement Behaviors at Scale. Journal of Physical Activity and Health 2025;22(10):1244 View
  4. Lawi A, Faizah A, Susanti , Toto G, Suaduon J, Gulo F. Integrating Mobile Apps and Wearables for Health Behavior Change: A Systematic Review. Engineering, Technology & Applied Science Research 2026;16(2):34581 View
  5. Rohl A, Fang U, Lund Rasmussen C, Hendry D, Doherty A, Straker L, Campbell A. Comparison of Deep Learning, Traditional Machine Learning, and Decision Tree Models for Activity Recognition in Children From Thigh-Worn Accelerometer Data. Journal for the Measurement of Physical Behaviour 2026;9(1) View
  6. Morud E, Koch M, Aanesen F, Redzovic S, Sundstrup E, Coenen P, Christensen I, Kleppe R, Merkus S. Hand-in-Hand–improving occupational health and quality of care in early education and care: study protocol for a cluster-randomized controlled trial. Frontiers in Public Health 2026;14 View