Dual-task walking for early detection of Alzheimer’s disease: comparative analysis of tasks using whole-body gait variables
This study underscores the benefits of incorporating gait variables of the upper body to enhance the performance of classification models for MCI detection. These insights could contribute to the development of more precise and practical screening tools for MCI.
Authors
- Kiyotaka Nemoto (ORCID: https://orcid.org/0000-0001-8623-9829)
- Tetsuaki Arai (ORCID: https://orcid.org/0000-0003-4355-3900)
- Yasunori Yamada (ORCID: https://orcid.org/0000-0003-3333-4368)
- Miho Ota (ORCID: https://orcid.org/0000-0001-8873-0822)
- Ken Takiyama
- Masatomo Kobayashi (ORCID: https://orcid.org/0000-0002-4397-8557)
- Kaoru Shinkawa (ORCID: https://orcid.org/0000-0002-3869-1922)
- Miyuki Nemoto (ORCID: https://orcid.org/0000-0002-1969-5098)
- Ryoto Katagiri
Institutions
- University of Tsukuba (JP)
- IBM Research - Tokyo (JP)
- Tokyo University of Agriculture and Technology (JP)
Publication Details
- Journal
- BMC Geriatrics
- Published
- 2025-10-24
- DOI
- https://doi.org/10.1186/s12877-025-06389-4
- Primary Topic
- Balance, Gait, and Falls Prevention
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Society for the Promotion of Science