Responsible translation of AI-driven pose estimation into post-stroke inpatient rehabilitation
Thematic Area: Health Care and Wellness
Faculty Mentors: One-U Responsible AI Initiative faculty fellow Maggie French, Department of Physical Therapy and Athletic Training; Scott Uhlrich, Department of Mechanical Engineering
Gait impairments after stroke are associated with increased fall risk, reduced independence, and diminished quality of life, yet traditional clinical assessments have only moderate associations with these measures and fail to comprehensively measure gait function. Emily Eichenlaub’s work examines how responsible AI can help patients at the bedside. She’ll deploy an affordable, scalable video-based motion capture system to more comprehensively quantify gait impairments for inpatients undergoing post-stroke rehabilitation. The system will use AI-driven pose estimation to provide new insights into patient recovery and inform clinical decision-making.
In May, Eichenlaub earned a Ph.D. from the University of North Carolina and North Carolina State University Lampe Joint Department of Biomedical Engineering. She holds a bachelor’s in the same field from the University of Delaware Honors College.
