Each year, more than 795,000 people in the U.S. suffer a stroke, about 75% of which are first strokes. Stroke is also the leading cause of serious disability and results in reduced mobility more than 50% of the time for survivors who are 65 and older, according to the CDC. University of Missouri researchers have developed technology using depth sensors and artificial intelligence to monitor and assess stroke patient recovery.

The depth sensors detect a 3D silhouette of the patient’s body and track movement. This system can be employed during rehab sessions, but also can be used to monitor patients going through normal daily activities in their own homes. According to Rachel Proffitt, MU School of Health Professions, the recovery assessment system not only recognizes patient activities but also evaluates their progress. Proffitt uses the information reported by the sensor system to adjust rehabilitation treatment plans as necessary. For example, according to Proffitt, if she observes that a patient stretches further or moves more smoothly through a range of motion, she can build greater challenges into the plan. If patients do not progress, Proffitt can dial back the activities accordingly.

Missouri College of Engineering professor of electrical engineering and computer science Majorie Skubic designed the depth sensor system and worked with graduate students to develop the evaluation algorithms. Further work at MSU involves creating tailored rehab exercises and routines to help individual patients progress in their recovery with activities that patients identify as most important to them.