PDWearML: Leveraging Daily Activities for Fast Parkinson's Disease Severity Assessment with Wearable Machine Learning
This work holds significant clinical value, offering a potential auxiliary tool for faster, more tailored interventions in PD healthcare. Code is availableat code ocean platform and https://github.com/wang-xulong/PDWearML.
Authors
- Po Yang
- Menghui Zhou (ORCID: https://orcid.org/0000-0001-8973-418X)
- Ming Xu (ORCID: https://orcid.org/0000-0002-2941-400X)
- Peng Yue
- Zhong Zhao (ORCID: https://orcid.org/0009-0009-7298-7469)
- Xulong Wang
- Zheyuan Xu
- Xiyang Peng
- Yun Yang
Institutions
- Yunnan University (CN)
- First People's Hospital of Yunnan Province (CN)
- University of Sheffield (GB)
Publication Details
- Journal
- IEEE Transactions on Biomedical Engineering
- Published
- 2025-12-25
- DOI
- https://doi.org/10.1109/tbme.2025.3648564
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00