Motif clustering and digital biomarker extraction for free-living physical activity analysis
This study introduced a novel approach to analyzing free-living PA data by identifying and characterizing specific activity patterns (motifs). The derived digital biomarkers provide a more nuanced understanding of PA and its impact on health, with potential applications in personalized health assessment and disease detection, offering a promising future for healthcare.
Authors
- Charlotte Wang (ORCID: https://orcid.org/0000-0002-6957-1579)
- Ya‐Ting Liang (ORCID: https://orcid.org/0000-0001-7852-0514)
Institutions
- National Taiwan University (TW)
- National Taipei University of Nursing and Health Science (TW)
Publication Details
- Journal
- BioData Mining
- Published
- 2025-01-22
- DOI
- https://doi.org/10.1186/s13040-025-00424-1
- Citations
- 2
- Primary Topic
- Time Series Analysis and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 2.97
Funders
- Ministry of Science and Technology, Taiwan
- National Science and Technology Council