Carleton University

Published purpose

Fall is a major concern in the elderly population often resulting in dire consequences. Vital signs often provide indication of the health status of the elderly. Most commercially available technologies for detecting and monitoring of vital signal and activities including fall are focused on single subject. Further vital signs are only monitored when the subject is still. Thus, the current technologies offer only limited monitoring. This project aims to provide monitoring of vital signs and activities including fall for multi-subject and ambulatory environment. The project suggests a radio frequency (RF)-based active sensing solution with multiple radars with ability to transmit different waveforms to handle both stationary and ambulatory monitoring conditions. Detection and monitoring of multi subject’s vital signs and activities including fall are achieved through advanced signal processing of the reflections obtained from the subjects going about during their activities and applying machine learning techniques for identifying activities including fall. The successful completion of the project will deliver a fall detection system capable of detecting and monitoring multiple moving subjects. This system will enable aging Canadians to age independently in the comforts of their home with a privacy preserving monitoring.