Project Overview

Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of death worldwide, affects 1 in 4 adults and is a disabling chronic disease that incurs high cost to the healthcare system. Even with optimal treatment, COPD patients frequently experience exacerbations or worsening of their condition and are sometimes hospitalized. Ideally, exacerbations would be treated early before becoming severe. We may be able to pre-empt exacerbations by using wearable technology that senses subtle abnormalities in physiological signals which herald early exacerbations.

Our goal is to improve the care of people with COPD and reduce hospitalizations by providing patients with a way to monitor their condition and detect early exacerbations, allowing for timely intervention. We are developing and validating sensors on wearable devices that will continually monitor vital signs, physical activity and coughing. We will improve the accuracy of the sensors to optimize its ability to detect subtle changes in factors known to be affected by COPD such as physical activity and coughing, and explore new factors such as heart rate and respiratory rate that may characterize early exacerbations. We will then collect data from COPD patients to train a machine-learning algorithm to determine what characteristics and combinations of these parameters herald an oncoming exacerbation.

Furthermore, we are conducting patient engagement interviews to determine what sort of device is useful, appealing and accessible for elderly patients with COPD. Our research also trains personnel in the exciting intersection of wearable development, machine learning and health care.

There are approximately 37,000 COPD hospitalizations annually in Ontario that have an average cost of $10,086 each. If this new technology succeeds in preventing even 1%, the potential savings are $3.7 million. Our hope is that this wearable sensing platform can eventually be used in other chronic diseases as well.