Facial Expression Analysis in Parkinson's Disease Using Machine Learning: A Review

Abstract

Computerised facial expression analysis is performed for a range of social and commercial applications and more recently its potential in medicine such as to detect Parkinson’s Disease (PD) is emerging. This has possibilities for use in telehealth and population screening. The advancement of facial expression analysis using machine learning is relatively recent, with majority of the published work being post-2019. We have performed a systematic review of the English-based publication on the topic from 2019 to 2024 to capture the trends and identify research opportunities that will facilitate the translation of this technology for recognising Parkinson’s disease. The review shows significant advancements in the field, with facial expressions emerging as a potential biomarker for PD. Different machine learning models, from shallow to deep learning, could detect PD faces. However, the main limitation is the reliance on limited datasets. Furthermore, while significant progress has been made, model generalization must be tested before clinical applications.