A newly developed technology can track and record the food consumed in long-term care homes. This can help reduce malnutrition and boost the overall health of residents of these places.
The system developed by researchers at University of Waterloo, University Health Network, and Schlegel-UW Research Institute for Aging uses AI application to examine photos of plates of residents after they eat.
The sophisticated software which studies depth, color, and other photo features can estimate the quantity of a type of food is consumed and compute its nutritional value.
At present, there is no way to determine if a resident ate only protein or only carbohydrates.
Importantly, the system is linked to recipes at the long-term care home, and using AI, keeps track of the quantity of each type of food consumed, and thus make sure each resident is consuming the specified amount of nutrients.
According to estimations, more than half the residents of long-term care homes suffer from malnutrition or are at the risk of malnutrition.
Food intake of residents is primarily observed by staff who use manual method to estimate the consumption by simply looking at the plates once residents finish eating. The process is subject to error rate of 50 percent or more, stated one of the research associates behind the technology.
By comparison of the two methods, the system provides accuracy within five percent, thereby providing detailed information on consumption patterns.
The development of the technology involved researchers to collaborate with personal support workers, long-term care workers, and dieticians to develop the system. The system provides benefits of saving time as well as accuracy, and would ideally be integrated with a tablet used by front-line staff to maintain electronic records.
