Mathematics professor Richard Sowers is part of a team that recently developed a new method for identifying symptoms of Parkinson's disease and multiple sclerosis, using a treadmill, digital cameras, and a machine learning algorithm to capture gait changes and abnormalities that are associated with these conditions. The results of this research, “A vision-based framework for predicting multiple sclerosis and Parkinson’s disease gait dysfunctions – a deep learning approach,” were published in Sowers is a co-author on the paper, along with Robert W. Motl, Rachneet Kaur and Manuel Hernandez.
Read the full story from the Illinois News Bureau.
More information about this gait analysis tool can be found in this article from Multiple Sclerosis News Today.