University of Waterloo

Published purpose

The project aims to develop technology to support aging in place through an integrated decision support for health and safety. A new nutritional tracking system will be developed, which leverages machine learning and computer vision algorithms to specifically reduce frailty risk and age-related muscle loss (sarcopenia) in elderly people. In particular, sources of protein, vitamin D and calcium as well as estimated intake of these nutrients will be analyzed. To this end, an e-screening tool for self-management and risk assessment will be developed along with machine learning methods to estimate both food volume and intake. To evaluate this intelligent tracking system, a food intake dataset including food weights, volume, amount intake, and image sensor measurements will be created over the course of the project. The project is a foundational step toward a longer-term project to work with older adults to facilitate aging in place by assessing and monitoring their food intake with their doctor/dietitian.