C-STAR: Automated Video Analysis of Motor Impairments


Artificial intelligence and sensing technologies are poised to transform healthcare and usher into the era of precision medicine. Deep learning, a sub-type of artificial intelligence, has now become a mature technology for identifying patterns in images and videos, including detecting a person and their body parts, and tracking movements and actions. This application could replace the complex setup of traditional motion capture, opening the door to automating the diagnosis and quantification of motor impairments inside and outside the clinic, using a device as simple as a smartphone. This on-demand webinar presents recent work on this topic and points out at some of the challenges that limit the current deployment of this technology as a clinical tool. Topics addressed include the applications of measuring Parkinsonian symptoms, evaluating risks of abnormal motor development in infants, and performing gait analysis using videos from a single camera.Instructor:

Instructor: Luca Lonini, PhD, Research Scientist II, Senior Data Scientist, Shirley Ryan AbilityLab; Research Assistant Professor, Department of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine

Targeted Audience: Researchers and clinicians interested in using technology to measure outcomes in a rehabilitation population 

Accreditation: None Offered


Online Learning