Unobtrusive Nighttime Movement Monitoring to Support Nursing Home Continence Care: Algorithm Development and Validation Study
The results from this study provide promising insights in unobtrusive nighttime movement monitoring. The study underscores the potential to enhance the quality of care for NH residents through a machine learning model based on data from accelerometers connected to a viscoelastic care mattress, thereby driving progress in the field of continence care and artificial intelligence-supported health care for older adults.
Authors
- Vero Vanden Abeele (ORCID: https://orcid.org/0000-0002-3031-9579)
- Bart Vanrumste (ORCID: https://orcid.org/0000-0002-9409-935X)
- Hans Hallez (ORCID: https://orcid.org/0000-0003-2623-9055)
- Chunzhuo Wang (ORCID: https://orcid.org/0000-0002-6992-7344)
- H. Strauven (ORCID: https://orcid.org/0000-0002-7233-8137)
Institutions
- Human Media (US)
- KU Leuven (BE)
Publication Details
- Journal
- JMIR Nursing
- Published
- 2024-09-23
- DOI
- https://doi.org/10.2196/58094
- Citations
- 4
- Primary Topic
- Pressure Ulcer Prevention and Management
- Type
- article
- Field-Weighted Citation Impact
- 6.87
Funders
- European Commission
- KU Leuven
- Vlaamse regering
- Erasmus+