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AI detects facial changes in Parkinson’s disease [ABOUT FACE]

The use of facial recognition software generally is contentious, prompting a wide range of reactions, from people concerned about privacy to others grateful that such software can help identify criminals or lost loved ones. But on the research front, the artificial intelligence (AI)-based technology can serve other purposes, such as potentially identifying Parkinson’s disease progression.

Parkinson’s is a neurodegenerative disorder that leads to symptoms such as shaking, stiffness and difficulty walking, as well as “facial masking,” which occurs when the affected person’s face has a mask-like expression, making it difficult for friends and family members to “read” what the person is feeling and for the individual to express him/herself by “making faces.”

Japanese researchers photographed 97 patients with Parkinson’s and 96 matched controls and fed the photos to AI software installed on a smartphone, which returned a set of attributes for each person, including age, gender, and type of emotion expressed.

By looking at the “age gap,” defined as the appearance age (as determined by the AI software) minus the real age, the scientists found that the appearance of patients with Parkinson's disease made them look older by an average of 2.4 years. For men, the average gap was even greater, at 3.4 years. Further, Parkinson’s patients were more likely to have expressionless faces and had significantly fewer happy faces.

While these findings might seem obvious to an affected individual’s friends and family, the fact that AI recognition software could detect these traits suggests that such software might be used down the road to help diagnose Parkinson’s disease and detect progression as mask-like features begin to occur.

Read the study here,


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