Apnea is a temporary stop in breathing and the most common type of apnea is Obstructive Sleep Apnea (OSA), which is a disturbance in sleep that is a leading cause in health problems such as heart disease, diabetes, high blood pressure, and Parkinson’s disease if left unnoticed or untreated. Importantly, 80% of people affected by OSA remain undiagnosed. In infants, a stop in breathing for 20 seconds becomes fatal. Current methods of detection of respiration in hospital settings are either quite invasive, with wires and electrodes attached on the body, or are very time-consuming, such as manual counting method and listening of changes in breathing patterns.

What if abnormal respiratory patterns can be detected non-invasively and provide early prediction of emergencies before they occur? This is the goal of Studio 1 Labs, a health technology company that has developed a responsive bed sheet using a noninvasive method of monitoring respiration patterns and changes in respiratory rate. Capturing millions of data points across a range of sensors, Studio 1 Labs is collaborating with Dr. Plinio Morita from the University of Waterloo, to develop a machine-learning algorithm for detection of respiration changes and to translate big data analysis into useful information, to provide patient-centered care for hospitals and homes.

Industry Partner(s):Studio 1 Labs Inc.

Academic Institution:University of Waterloo

Academic Researcher: Plinio Morita

Focus Areas: Advanced Manufacturing, Health

Platforms: Cloud, GPU