The SDMT test can be used to measure cognitive decline in patients with multiple sclerosis (MS) However, the usual test requires manual effort, which in MS patients may be compromised, and so interfere with the test. Our collaborator, Dr. Anthony Feinstein, developed a computer-based test that did not require physical movement, but still needed a human operator to advance the test, described here. In this project, we developed a hands-free fully automated SDMT test that uses voice recognition to determine accuracy of the responses, and when to advance the screen.
In collaboration with several clinics, we are now confirming the validity of this method, as wel as establishing clinical norms for diagnosis.
Collaborators: Dr. Anthony Feinstein, Sunnybrook Hospital and the University of Toronto
Student (graduated, but still collaborating): Lingkai Shen
In a different collaboration, with Professor Moshe Eizenman, we sought to develop an eye tracking system that could work on a mobile device. The long-term goal was to use mobile eye tracking for various cognitive, physiological and mental health screening and measurement, which Professor Eizenman continues.
Collaborator: Professor Moshe Eizenman
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering,
Faculty of Applied Science and Engineering, University of Toronto