Can Parkinson’s disease be detected through facial expressions?

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Author: Johanna Stiefler JohnsonPublished: 23 September 2021

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A man smiles in the mirror.

US researchers have used an artificial intelligence (AI) tool to detect Parkinson’s through the analysis of facial expressions.

The team collected 1,812 videos featuring 604 people; 543 of these participants didn’t have Parkinson’s while 61 did. They were recorded making three facial expressions – disgust, surprise and a smile – followed by a neutral expression. Measuring these in terms of “micro-expressions”, the AI tool found that people with Parkinson’s had fewer facial muscle movements than those without.

The researchers used this information to train a machine learning tool to distinguish between people with and without the condition. It was able to identify Parkinson’s in individuals with 95.6% accuracy.

Reflecting on the tool’s “potential to be an important digital biomarker” for the condition, the team wrote: “An algorithm’s ability to analyse the subtle characteristics of facial expressions, often invisible to a naked eye, adds significant new information to a neurologist.”


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