Monitoring the progression of multiple sclerosis-related gait issues can be challenging in adults over 50 years old, requiring a clinician to differentiate between problems related to MS and other age-related issues. To address this problem, researchers are integrating gait data and machine learning to advance the tools used to monitor and predict disease progression. A new study of this approach led by University of Illinois Urbana Champaign graduate student Rachneet Kaur,  Carle Illinois College of […]