7 papers
Every Step of the Way: Video-based Parkinsonian Turning Step Counting
Qiushuo Cheng, Jingjing Liu, Catherine Morgan +2
As a prominent symptom of Parkinson's disease (PD), turning impairment is evaluated through parameters such as turning angle, duration, and particularly, the number of steps requir…
TraMP-LLaMA: Generative Interpretability with Decoupled Instruction Tuning for Facial Expression Quality Assessment
Shuchao Duan, Alan Whone, Hossein Rahmani +2
Existing facial expression quality assessment (FEQA) methods typically produce only a severity score, without explicitly communicating the observable facial motion evidence that su…
Skeleton-Snippet Contrastive Learning with Multiscale Feature Fusion for Action Localization
Qiushuo Cheng, Jingjing Liu, Catherine Morgan +2
The self-supervised pretraining paradigm has achieved great success in learning 3D action representations for skeleton-based action recognition using contrastive learning. However,…
GAITGen: Disentangled Motion-Pathology Impaired Gait Generative Model -- Bringing Motion Generation to the Clinical Domain
Vida Adeli, Soroush Mehraban, Majid Mirmehdi +6
Gait analysis is crucial for the diagnosis and monitoring of movement disorders like Parkinson's Disease. While computer vision models have shown potential for objectively evaluati…
CARE-PD: A Multi-Site Anonymized Clinical Dataset for Parkinson's Disease Gait Assessment
Vida Adeli, Ivan Klabucar, Javad Rajabi +25
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 publi…
Your Turn: At Home Turning Angle Estimation for Parkinson's Disease Severity Assessment
Qiushuo Cheng, Catherine Morgan, Arindam Sikdar +3
People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease progresses. Existing clinical rating t…