aceQuantitative Assessment of Facial Expression Asymmetry in Parkinson's Disease
Objective Hypomimia, or reduced facial expressiveness, is a cardinal motor feature of Parkinson's disease (PD). Although limb motor symptoms in PD are characteristically asymmetric, whether facial hypomimia exhibits comparable asymmetry remains poorly understood. We investigated facial expression asymmetry in PD using AI-based computer vision and machine learning. Methods Videos of instructed emotional facial expressions were collected from 101 individuals with PD and 94 healthy controls (HCs) across two indepen…
Static and dynamic features derived from these indices were compared between groups and used to train machine learning models for PD-HC discrimination, with each model trained and evaluated separately within each cohort.
Sources
- Peer-reviewedJournal of Movement Disorders2026-09-22
What do you make of this one?
Truvace Impact Record TRV-2026-1175, v2: “Quantitative Assessment of Facial Expression Asymmetry in Parkinson's Disease.” Truvace, 2026-10-26. /record/TRV-2026-1175 (accessed on the day you copy it). sha256 bc3ad8d20c6f2911…
Change history
Every change made to this record since it was first published, and why.
Direction audit: the problem line stated no AI consequence and was removed. Filed as context; not counted as a gain or a problem.
Certified into the record
How to check it yourself, without trusting this page
Download any version from /api/record/TRV-2026-1175 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.