Prediction of safety accident subtypes for persons with dementia using sensors and machine learning: an observational study
These findings highlight the potential of these technologies to identify high-risk individuals with dementia. Further research is recommended to integrate these methods for daily safety monitoring of this population.
Authors
- A Young Cho (ORCID: https://orcid.org/0009-0006-2977-5397)
- Eunjin Yang (ORCID: https://orcid.org/0000-0002-8669-954X)
- Ji Yeon Lee (ORCID: https://orcid.org/0000-0003-1159-6068)
- Kyung Hee Lee (ORCID: https://orcid.org/0000-0003-2964-8356)
- Yeji Jang (ORCID: https://orcid.org/0009-0006-2936-5259)
- SungHee Lee (ORCID: https://orcid.org/0000-0002-4360-1565)
- Yong-Sung Choi (ORCID: https://orcid.org/0009-0008-2628-3738)
Institutions
- University of Seoul (KR)
- Gachon University (KR)
- Inha University (KR)
- Yonsei University (KR)
Publication Details
- Journal
- The Gerontologist
- Published
- 2025-12-17
- DOI
- https://doi.org/10.1093/geront/gnaf313
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00