{"ID":2860379,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.04312","arxiv_id":"2510.04312","title":"CARE-PD: A Multi-Site Anonymized Clinical Dataset for Parkinson's Disease Gait Assessment","abstract":"Objective gait assessment in Parkinson's Disease (PD) is limited by the absence of large, diverse, and clinically annotated motion datasets. We introduce CARE-PD, the largest publicly available archive of 3D mesh gait data for PD, and the first multi-site collection spanning 9 cohorts from 8 clinical centers. All recordings (RGB video or motion capture) are converted into anonymized SMPL meshes via a harmonized preprocessing pipeline. CARE-PD supports two key benchmarks: supervised clinical score prediction (estimating Unified Parkinson's Disease Rating Scale, UPDRS, gait scores) and unsupervised motion pretext tasks (2D-to-3D keypoint lifting and full-body 3D reconstruction). Clinical prediction is evaluated under four generalization protocols: within-dataset, cross-dataset, leave-one-dataset-out, and multi-dataset in-domain adaptation. To assess clinical relevance, we compare state-of-the-art motion encoders with a traditional gait-feature baseline, finding that encoders consistently outperform handcrafted features. Pretraining on CARE-PD reduces MPJPE (from 60.8mm to 7.5mm) and boosts PD severity macro-F1 by 17 percentage points, underscoring the value of clinically curated, diverse training data. CARE-PD and all benchmark code are released for non-commercial research at https://neurips2025.care-pd.ca/.","short_abstract":"Objective gait assessment in Parkinson's Disease (PD) is limited by the absence of large, diverse, and clinically annotated motion datasets. We introduce CARE-PD, the largest publicly available archive of 3D mesh gait data for PD, and the first multi-site collection spanning 9 cohorts from 8 clinical centers. All recor...","url_abs":"https://arxiv.org/abs/2510.04312","url_pdf":"https://arxiv.org/pdf/2510.04312v1","authors":"[\"Vida Adeli\",\"Ivan Klabucar\",\"Javad Rajabi\",\"Benjamin Filtjens\",\"Soroush Mehraban\",\"Diwei Wang\",\"Hyewon Seo\",\"Trung-Hieu Hoang\",\"Minh N. Do\",\"Candice Muller\",\"Claudia Oliveira\",\"Daniel Boari Coelho\",\"Pieter Ginis\",\"Moran Gilat\",\"Alice Nieuwboer\",\"Joke Spildooren\",\"Lucas Mckay\",\"Hyeokhyen Kwon\",\"Gari Clifford\",\"Christine Esper\",\"Stewart Factor\",\"Imari Genias\",\"Amirhossein Dadashzadeh\",\"Leia Shum\",\"Alan Whone\",\"Majid Mirmehdi\",\"Andrea Iaboni\",\"Babak Taati\"]","published":"2025-10-05T18:14:50Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","project_urls":"[\"https://neurips2025.care-pd.ca/\"]","has_code":false,"code_links":[{"ID":608722,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2860379,"paper_url":"https://arxiv.org/abs/2510.04312","paper_title":"CARE-PD: A Multi-Site Anonymized Clinical Dataset for Parkinson's Disease Gait Assessment","repo_url":"https://github.com/TaatiTeam/CARE-PD","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0},{"ID":608723,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2860379,"paper_url":"https://arxiv.org/abs/2510.04312","paper_title":"CARE-PD: A Multi-Site Anonymized Clinical Dataset for Parkinson's Disease Gait Assessment","repo_url":"https://github.com/nerfies/nerfies.github.io","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}