Using Digital Cameras and Machine Learning to Identify Neurological Diseases
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, University of Illinois Urbana-Champaign Professor of Kinesiology and Community Health, who led the project with graduate student Rachneetkaur and Industrial and Enterprise Systems Engineering and Mathematics professor Richard Sowers.