Detroit Jan. 22, 2018 – An Israeli startup specializing in neurological disorders is the winner of Henry Ford Health System’s first ever artificial intelligence (AI) challenge. Montfort (Mon4T) has developed a real-time brain monitor that uses smartphone technology to conduct, record and analyze data from tests for patients with various neurological disorders.

Henry Ford Innovations, the multi-disciplinary team responsible for leveraging Henry Ford’s intellectual property, issued the challenge last fall as part of its Global Technology Development Program now underway in Israel. Backed by a generous grant from the William Davidson Foundation, the program is designed to identify cutting-edge healthcare technologies from Israel and co-develop and launch them in the U.S. healthcare market. Montfort was chosen from a pool of nearly 50 applicants.

“Henry Ford has long been an international leader in neurosciences research and treatment and that makes Montfort a great fit for this challenge,” said Scott Dulchavsky, M.D., Ph.D., CEO of the Henry Ford Innovation Institute and Chairman of Surgery and Surgeon in Chief at Henry Ford Hospital. “Our physicians are excited to partner with them toward AI and machine learning solutions that will ultimately benefit our patients.”
Available for both iOS and Android, Montfort’s master application uses the smartphone’s integral sensors including accelerometers, gyroscopes, and touchscreen to record and analyze patient data from a panel of neurological tests for patients with conditions like Parkinson’s disease and Normal Pressure Hydrocephalus (NPH). This information is processed through machine learning paradigms to answer questions working through large data sets. Montfort’s application is available in two versions: a clinical app for use by the patient’s care team and a home or consumer version, in which patients can use their own smartphones to perform some of the tests.

Peter LeWitt, M.D., Director of the Parkinson’s disease and Movement Disorders Program at Henry Ford Hospital, said these applications have a lot of promise for research and improved clinical care. “For patients with movement disorders, we are in need of multi-modality data analysis to enhance clinical decisions and reports from patients. Machine learning applications offering such detailed and unbiased analysis have the potential to guide understanding of movement disorders that even a trained clinician might miss – and that could greatly advance our capabilities for both diagnosis and treatment.”

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