SUNY Canton Faculty Member Puts Eyes on Early Detection of Alzheimer's Disease
Canton, NY (06/24/2025) — A SUNY Canton researcher sees the future of Alzheimer's disease diagnosis and treatment in people's eyes.
Assistant Professor Mehdi Ghayoumi, Ph.D., recently received a $50,000 National Science Foundation (NSF) I-Corps grant to market an advanced eye-tracking system to detect indicators of neurodegeneration. The system will analyze eye movement data to identify subtle ocular biomarkers suggesting cognitive decline.
"Our project leverages cutting-edge machine learning techniques for early detection," Ghayoumi said. "The system captures and analyzes complex temporal patterns in eye movement data, offering a precise, non-invasive and cost-effective diagnostic method that can revolutionize Alzheimer's disease diagnosis and treatment."
Research has shown that Alzheimer's disease can affect how people move and focus their eyes. These changes happen because parts of the brain that control eye movements and thinking skills become damaged, including areas responsible for attention, coordination, and understanding visual information, according to Ghayoumi.
Even though scientists have found strong signs that eye movement patterns can help detect Alzheimer's disease, doctors do not yet widely use these methods. This is mostly because there are no standard testing procedures, reliable data analysis tools, or approved systems that doctors can use with confidence in real-world settings "Our project addresses this gap by developing a sophisticated eye-tracking system to identify early indicators of the disease," he said.
Eye movement information is collected using web-based software and a standard webcam to collect and manage users' wellness data. It then uses artificial intelligence (AI) and machine learning to provide insight.
As one of the college's foremost AI experts, Ghayoumi explained that this analysis tool uses advanced approaches. These techniques help the system interpret patterns in user behavior over time, enabling more accurate insights and tailored mental health recommendations.
The research team, which also includes Cybersecurity Professor Kambiz Ghazinour and SUNY Canton student research assistants, has completed more than 200 interviews with neurologists, mental health clinicians, researchers, caregivers, senior care facility directors, and healthcare administrators to refine their understanding of how their approach could fit into current diagnostic strategies.
"By validating the real-world applicability of this technology, we hope to position it for future development better and, ultimately, improve access to early screening tools for cognitive and mental health conditions," Ghayoumi said.
The Alzheimer's component is one facet of Ghayoumi's MediMood proprietary software offered through his company, AllGalaxy. MediMood proprietary algorithms analyze behavioral patterns and user input. The pioneering platform offers real-time feedback and personalized wellness recommendations.
Having already developed the technology, the funding secured from NSF I-Corps will support the team's customer discovery portion of the commercial project's potential to offer the assessment tool. The team now plans to rigorously explore and validate the real-world needs and potential adoption paths for their product.
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Eye Tracking – Using a web camera and proprietary health software, SUNY Canton Assistant Professor Mehdi Ghayoumi can analyze eye movement data to identify subtle biomarkers suggesting cognitive decline. The faculty member recently received a $50,000 National Science Foundation (NSF) I-Corps grant to market the innovation.