Five winners – three in the Canadian stream and two in the U.S. stream – have been selected as winners of the Healthy Behaviour Data Challenge.
The group: RTI International is an independent, 501(c)(3) nonprofit institute that provides objective research, development and technical services to government and private-sector clients. RTI’s Digital Health and Clinical Informatics Program conducts research on patient and clinician use of technology to improve individual and population health, self-management, and provider-based health care as part of health system transformation. […]
The group: Onlife Health is a data-driven health solutions company. Its engagement platform empowers more than 11 million people to take an active and ongoing role in their own health. It leverages sophisticated data analytics to engage users in meaningful programs and to understand population health. The idea: Simplify and improve the quality and quantity […]
The group: The Stremler research lab at the University of Toronto focuses on improving sleep and related health outcomes for children and parents. The idea: The PHASStrak System entails an inexpensive Bluetooth accelerometer, smartphone app and cloud-based automated analysis pipeline using research-validated algorithms to concurrently generate objective measures of sleep, physical activity and sedentary behaviour. […]
The group: The Ubiquitous Health Technology Lab (UbiLab) at the University of Waterloo designs, develops and evaluates technologies that can be used with minimal burden to the user, providing maximum reliability and an outstanding user experience. UbiLab’s mission is to leverage wearable, Internet of Things and mobile health technologies for population-level surveillance. The idea: This project […]
Social Health Lab
The group: The Social Health Lab at the University of British Columbia conducts research to understand and improve social connectedness, well-being, and physical and mental health. The idea: This project uses a smartphone app to predict important sleep parameters solely from natural phone use, and it validates this approach against objectivelyassessed indicators of sleep quality. […]