Machine Learning and Digital Cameras to Identify Neurological Disorders

Machine learning and digital cameras are used by a team to predict neurological diseases

Researchers used digital cameras in an attempt to simplify the diagnosis of patients with Parkinson’s and multiple sclerosis. They captured changes in gait, a symptom of both diseases. They then developed a machine learning algorithm that could distinguish between people with MS and PD and those without these neurological conditions.

IEEE Journal of Biomedical and Health Informatics has published their findings.

The research aimed to make diagnosing these diseases easier, according to Manuel Hernandez, professor of kinesiology at the University of Illinois Urbana-Champaign, who worked with graduate student Rachneet Kour and Richard Sowers, professor of industrial and enterprise system engineering and mathematics.