New technology could help reduce malnutrition and improve overall health in long-term care (LTC) homes by automatically recording and tracking how much food residents consume.
The smart system, developed by engineering and health researchers at the University of Waterloo, the Schlegel-UW Research Institute for Aging and the University Health Network (UHN), uses artificial intelligence (AI) software to analyze photos of plates of food after residents have eaten.
The sophisticated software, which examines colour, depth and other features of photos, can estimate how much of each kind food has been consumed and calculate its nutritional value.
“Right now, there is no way to tell whether a resident ate only their protein, or only their carbohydrates,” said Kaylen Pfisterer, who co-led the research with her husband and fellow alumnus, Robert Amelard, while earning a PhD in systems design engineering at Waterloo.
“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.”
Go to Food-tracking AI system developed to reduce malnutrition in LTC homes for the full story.