As a biomedical engineering lab, we work with clinicians to translate our research findings to clinical applications. We work with a broad range of clinicians from sleep medicine, sports medicine, and rehabilitation to use our tools for measuring human motion in the wild to better assess and monitor patient well being.
We are always looking for motivated students to bridge the gap between the engineering and clinical worlds.
Sleep is one of the most important functions for human health and well being. Inadequate sleep can result in a loss of focus, slow reactions, and generally lower cognitive function during the day. Currently, there are several conditions that affect the quality and quantity of sleep, including sleep apnea and restless leg syndrome, however these can only be diagnosed by clinicians following observation in a sleep laboratory with polysomnography. This procedure is inconvenient, intrusive, and time consuming. Thus, we are working with clinicians at BC Children's Hospital to develop automated techniques to detect and classify restless motions both during sleep and during wake periods to help diagnose and treat patients.
Here, we are using standard monocular video footage (like from a cell phone camera) to observe patients in either a specific assessment task, or in their natural environment. Using automated segmenting software (Open Pose), we can track the skeletal motions of the participants and identify and classify motions using logistic regression or support vector machines. Automated motion detection can drastically reduce the time required by clinicians to observe participants and allow continuous monitoring in home settings.