Objective assessment of gait and posture symptoms in Parkinson’s disease using wearable sensors and machine learning
This study demonstrates the feasibility of using wearable sensor data to objectively assess gait and posture symptoms in PD. Though conducted in a clinical setting, the approach may support clinicians through consistent assessments and more frequent monitoring, with potential for future home-based use to enable longitudinal symptom tracking.
Authors
- Shinuan Lin
- Kang Ren (ORCID: https://orcid.org/0000-0002-1675-0805)
- Yun Ling (ORCID: https://orcid.org/0000-0001-7009-2818)
- Jianing Jin (ORCID: https://orcid.org/0000-0002-2960-783X)
- Tao Feng (ORCID: https://orcid.org/0000-0002-0378-7764)
- Xuemei Wang (ORCID: https://orcid.org/0009-0002-8495-5922)
- Zhonglue Chen (ORCID: https://orcid.org/0000-0001-7037-2481)
- Lingyan Ma (ORCID: https://orcid.org/0000-0001-7961-1426)
- Fei Hu Zhang (ORCID: https://orcid.org/0000-0003-4579-6797)
- Zhan Wang (ORCID: https://orcid.org/0000-0002-6712-2286)
Institutions
- Capital Medical University (CN)
- Chinese Institute for Brain Research (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Frontiers in Aging Neuroscience
- Published
- 2025-08-08
- DOI
- https://doi.org/10.3389/fnagi.2025.1618764
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality
- Beijing Municipal Science and Technology Commission
- Science and Technology Planning Project of Shenzhen Municipality