Possible new tech could help reduce malnutrition, improving overall health in long-term care homes using Artificial Intelligence
Developed by researchers at the University of Waterloo, the Schlegel-UW Research Institute for Aging and the University Health Network, the smart system will record and track how much food residents consume, enabling Artificial Intelligence to potentially solve the long running issue of malnutrition in care homes.
The AI software will analyse photos of plates of food after residents have eaten, it will examine colour, depth and other photo features in order to estimate how much of each kind of food has been eaten and then calculate its nutritional value.
“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” said Kaylen Pfisterer, who co-led the research while earning a PhD in systems design engineering at Waterloo.
Malnutrition in care homes
It is estimated that more than half of residents of long-term care homes are either malnourished or at risk of malnutrition.
“Right now, there is no way to tell whether a resident ate only their protein or only their carbohydrates,” said Kaylen Pfisterer. Currently food intake is primarily monitored by staff who manually record estimates of consumption by looking at plates once residents have finished eating.
Robert Amelard, a Waterloo alumnus said the subjectivity of the current process results in an error rate of 50% or more. This could have catastrophic consequences on patients wellbeing and perpetuating the current issue of malnutrition in care homes.
By comparison, the automated system is accurate to within 5%, “providing fine-grained information on consumption patterns.”
Researchers collaborated with personal support workers, dieticians, and other long-term care workers to develop the system. As well as saving time and improving accuracy it may be able to be added to tablet computers already used by front-line staff to keep electronic records therefore streamlining its introduction into the care home system.
“My vision would be to monitor and leverage any changes in food intake trends as yellow or red flags for the health status of residents more generally and for monitoring infection control,” said Pfisterer, now a scientific associate at the University Health Network Centre for Global eHealth Innovation.
The full research paper is available here titled, Automated food intake tracking requires depth-refined semantic segmentation to rectify visual-volume discordance in long-term care homes, and appears in the journal Scientific Reports.