Food-tracking AI system developed to reduce malnutrition in LTC homes

Returning to in-person experiences in February: for more information. New technology automatically records and tracks how much food residents consume New technology could help reduce malnutrition and improve overall health in long-term care homes by automatically recording and tracking how much food residents consume. The smart system, developed by researchers at the University of Waterloo, the Schlegel-UW Research Institute for Aging and the University Health Network, uses artificial intelligence software to analyze photos of plates of food after residents have eaten. The sophisticated software, which examines colour, depth, and other photo features, can estimate how much of each kind of 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, 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." It is estimated that more than half of residents of long-term care homes are either malnourished or at risk of malnutrition. Food intake is now primarily monitored by staff who manually record estimates of consumption by looking at plates once residents have finished eating.