BRIEF RESEARCH REPORT article
Front. Neurol.
Sec. Movement Disorders
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1661043
This article is part of the Research TopicAI-powered Advances in Diagnosis and Management of Movement DisordersView all articles
Facial Expression Analysis to Uncover the Relationship Between Sialorrhea and Hypomimia in Parkinson's Disease
Provisionally accepted- 1Gangneung Asan Hospital, Seoul, Republic of Korea
- 2UBC Hospital Pacific Parkinson's Research Centre, Vancouver, Canada
- 3The University of British Columbia Department of Medicine, Vancouver, Canada
- 4Radboud Universiteit, Nijmegen, Netherlands
- 5School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
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Sialorrhea, or excessive drooling, is a prevalent yet frequently under-recognized non-motor symptom of Parkinson's disease (PD). Hypomimia, or reduced facial expressivity, constitutes another significant feature of PD. Although previous studies have suggested a potential clinical association between these two disease features, this relationship has seldom been quantified using artificial intelligence (AI) methodologies. In this study, we sought to characterize the association between hypomimia and sialorrhea in PD using both traditional clinical scales and AI-based video analysis. We conducted a cross-sectional study involving 52 individuals diagnosed with PD. Sialorrhea severity was assessed using the Radboud Oral Motor Inventory for Parkinson's Disease–Saliva subscale (ROMP-saliva), while hypomimia was evaluated via the Unified Parkinson's Disease Rating Scale (UPDRS). Facial video recordings were acquired and analyzed using AI algorithms to extract key facial landmarks. These landmarks were processed into 20 quantitative features representing the mouth, eyes, and combined facial regions. To assess the relationship between facial expressivity and sialorrhea severity, we employed Principal Component Analysis, Canonical Correlation Analysis, and bootstrapping. Clinical rating scales demonstrated a modest correlation between hypomimia and drooling severity (r = 0.368, p = 0.007). In contrast, video analysis revealed moderate correlations between ROMP-saliva scores and features derived from the mouth (mean r = 0.600), eyes (mean r = 0.641), and combined facial regions (mean r = 0.575). These findings support a quantifiable association between hypomimia and sialorrhea in PD and underscore the utility of quantitative facial analysis for the automated detection of under-recognized non-motor symptoms such as drooling.
Keywords: Parkinson's disease, drooling, Sialorrhea, Hypomimia, artificial intelligence
Received: 07 Jul 2025; Accepted: 03 Oct 2025.
Copyright: © 2025 Park, Serbée, Irani, Mirian, Castaneda, Grundy and McKeown. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Martin J McKeown, martin.mckeown@ubc.ca
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