Gait analysis in the early stage of Parkinson’s disease with a machine learning approach
The non-contact gait assessment system facilitates the objective and quantitative evaluation of gait disorder in PD patients, effectively distinguishing those in the early stage from healthy individuals. The system holds significant potential for the early detection of PD. It also harnesses gait parameters for a reasoned prediction of the MDS-UPDRS III score, thereby quantifying disease severity. Overall, gait assessment is a valuable method for the early identification and ongoing monitoring of PD.
Authors
- Xiangmin Fan (ORCID: https://orcid.org/0000-0003-4223-2320)
- Wenchao Yin (ORCID: https://orcid.org/0009-0001-0442-7752)
- Cui Wang (ORCID: https://orcid.org/0000-0002-8070-5574)
- Hong Gao (ORCID: https://orcid.org/0000-0002-3469-7526)
- Xiaohui Niu (ORCID: https://orcid.org/0000-0001-6801-2030)
- Wencheng Zhu (ORCID: https://orcid.org/0009-0001-9805-6584)
- Chenxin Shen
Institutions
- Chinese Academy of Sciences (CN)
- Dalian University of Technology (CN)
- Dalian Municipal Central Hospital (CN)
- Institute of Software (CN)
- Dalian Maritime University (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2024-10-07
- DOI
- https://doi.org/10.3389/fneur.2024.1472956
- Citations
- 15
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 5.54