Detection of sedentary time and bouts using consumer-grade wrist-worn devices: a hidden semi-Markov model
STEPHEN can characterize the proportion of time spent being sedentary and usual sedentary bout length. The methodology is available as an open access R package available from https://github.com/limfuxing/stephen/ . The package includes trained models, but users have the flexibility to train their own models.
Authors
- Erin J. Howden (ORCID: https://orcid.org/0000-0002-6657-4395)
- Agus Salim (ORCID: https://orcid.org/0000-0003-3999-7701)
- David Wayne Dunstan (ORCID: https://orcid.org/0000-0003-2629-9568)
- Hayley T. Dillon (ORCID: https://orcid.org/0000-0002-3783-7993)
- Howard D. Bondell (ORCID: https://orcid.org/0000-0001-7743-0840)
- Elisabeth Winkler (ORCID: https://orcid.org/0000-0003-1452-6102)
- Julie Anne Simpson (ORCID: https://orcid.org/0000-0002-2660-2013)
- Christian John Brakenridge (ORCID: https://orcid.org/0000-0001-6022-7539)
- Neville G. Owen (ORCID: https://orcid.org/0000-0003-2784-4820)
- Genevieve Nissa Healy (ORCID: https://orcid.org/0000-0001-7093-7892)
- Ruth Grigg (ORCID: https://orcid.org/0000-0003-1661-4931)
- Dulari Hakamuwa Lekamlage
Institutions
- Baker Heart and Diabetes Institute (AU)
- Deakin University (AU)
- The University of Queensland (AU)
- The University of Melbourne (AU)
- Finland University (FI)
- South Eastern Finland University of Applied Sciences (FI)
- Swinburne University of Technology (AU)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1186/s12874-024-02311-5
- Primary Topic
- Physical Activity and Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- State Government of Victoria
- National Health and Medical Research Council