Automated Video Analysis of Motor Impairments, a Webinar by 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
Saturday, March 20, 2021 at 11:00am (Central Time)
Artificial intelligence and Sensing technologies are poised to transform healthcare and usher in the era of precision medicine. Deep learning in particular, a subtype 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 their 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. I will present our recent work on this topic and show applications towards evaluating Parkinson’s symptoms, assessing risks of atypical motor development in infants and performing gait analysis from mobile phone videos.
Luca Lonini is a Senior Research Scientist and Data Scientist in the Office of Translational Research at the Shirley Ryan AbilityLab, and a Research Assistant Professor in the Department of Physical Medicine and Rehabilitation at Northwestern University. His research is focused on wearable computing and contactless sensing to quantify rehabilitation outcomes and help clinicians deliver personalized care. He was formerly a Postdoctoral researcher in the Max Nader Lab and then a Motion Scientist at Apple, where he worked on applications of wearable technology and machine learning to monitor the progression of diseases affecting mobility. He published in interdisciplinary venues merging computer science, engineering and clinical research, on topics ranging from Parkinson’s symptom monitoring, fall detection and stroke patient mobility using wearable technology.
Register for the Webinar at this link.