Carleton University

Published purpose

Healthy and safe aging in place requires a continuous assessment of well-being. Automating this assessment is a cost-effective solution that reduces the burden on family members and caregivers. This project proposes deploying ambient sensors in the home and using an integrated decision support system to combine the information from these sensors and assess the health and well-being of the home occupant. The system will monitor cough, vital signs (heart rate, breathing rate) and daily activities using data analysis, deep learning and machine learning methods. The result is an integrated decision support software system that can detect any decline in health conditions, help in the early detection of diseases and enable early intervention. The project will lead to a cost-effective approach to enable aging in place by providing high-quality healthcare, reducing the burden on family members, and reducing the need for long term care, in support of the NRC AiP program.