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  • Team uses digital cameras, machine learning to predict neurological disease

    Researchers stand alongside an elongated treadmill used in the research.

    From left, Richard Sowers, Rachneet Kaur and Manuel Hernandez led the development of a new approach for identifying people with multiple sclerosis or Parkinson’s disease. Their method involves videotaping the hips and lower extremities of individuals walking on a treadmill and allowing a machine-learning algorithm to differentiate gait abnormalities associated with each of these neurological conditions.

    Photo by Fred Zwicky

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  • Editor’s notes

    To reach Manuel Hernandez, email mhernand@illinois.edu.
    To reach Rachneet Kaur, email rk4@illinois.edu.
    To reach Richard Sowers, email r-sowers@illinois.edu.

    The paper “A vision-based framework for predicting multiple sclerosis and Parkinson’s disease gait dysfunctions – a deep learning approach” is available online and from the U. of I. News Bureau.

    DOI: 10.1109/JBHI.2022.3208077