Communications of the ACM
Food-Tracking AI System to Reduce Malnutrition in LTC Homes
The smart system uses artificial intelligence software to analyze photos of plates of food after residents have eaten.
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Researchers at Canada's University of Waterloo, the Schlegel-UW Research Institute for Aging, and the University Health Network have developed a smart system that uses artificial intelligence to track food consumption by residents of long-term care (LTC) communities.
The system analyzes photos of plates of food to estimate how much of each kind of food was eaten and calculate its nutritional value.
Waterloo's Kaylen Pfisterer said, "Right now, there is no way to tell whether a resident ate only their protein or only their carbohydrates. Our system is linked to recipes at the long-term care home and, using artificial intelligence, keeps track of how much of each food was eaten to make sure residents are meeting their specific nutrient requirements."
The researchers found the smart system to be accurate to within 5%, compared to error rates of 50% or more associated with manual consumption estimates recorded by staff.
From University of Waterloo News (Canada)
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