#11 - The Smile Test: How AI Detects Parkinson's Disease

Code & Cure

Can a smile reveal the early signs of Parkinson’s disease?

New research suggests it can—and AI is making that detection possible. Scientists are training machine learning systems to spot subtle facial changes associated with Parkinson’s, particularly in how we smile. These early signs, often missed by the human eye, could hold the key to faster, more accessible diagnosis.

Parkinson’s typically presents with tremors, muscle rigidity, and slowed movement. But it also affects facial muscles, leading to “hypomimia”—a loss of expressiveness where smiles become slower, less intense, and less spontaneous. Using the Facial Action Coding System, researchers broke down these expressions into measurable muscle movements like the “lip corner puller” and “dimpler,” allowing AI to analyze them with clinical precision.

Interestingly, models trained specifically on smile-related features outperformed those using broader facial data, showing that a targeted approach may yield better diagnostic results. This innovation blends expert medical knowledge with AI—not as a mysterious black box, but as a transparent and focused tool for real-world screening.

While promising, the technology isn’t without challenges. False positives and issues with lighting, camera quality, and cultural differences in facial expressions highlight the need for more testing before widespread use. Still, in clinical settings, especially where neurologists are scarce, this tool could offer meaningful support.

Tune in to explore how artificial intelligence is helping decode the smallest of human expressions—and what that might mean for the future of neurological care.

References:

AI‑Enabled Parkinson’s Disease Screening Using Smile Videos
T. Adnan, et al.
NEJM AI, 2025

Automated video-based assessment of facial bradykinesia in de-novo Parkinson’s disease
Michal Novotny et al.
npj, Nature Digital Medicine, 2022

Detection of hypomimia in patients with Parkinson’s disease via smile videos
G. Su, et al.
Annals of Translational Medicine, 2021

Analysis of facial expressions in parkinson's disease through video-based automatic methods
Andrea Bandini et al
Journal of Neuroscience Methods, 2017

Credits:

Theme music: Nowhere Land, Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 4.0
https://creativecommons.org/licenses/by/4.0/

บท

1. Introduction to Facial Expressions (00:00:00)

2. Understanding Parkinson's Disease Motor Features (00:01:42)

3. Facial Expression Changes in Parkinson's (00:03:30)

4. AI Systems for Facial Recognition (00:06:35)

5. The Facial Action Coding System (00:11:02)

6. Smile Features as Key Indicators (00:15:10)

7. Real-world Application Challenges (00:21:10)

8. Future Directions and Potential (00:25:13)