About Speaker

Professor George Demiris is a PIK (Penn Integrates Knowledge) University Professor at the University of Pennsylvania and holds joint faculty appointments in the Department of Biobehavioral Health Sciences of the School of Nursing where he serves as Associate Dean for Research and Innovation, and the Informatics Division of the Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine. He explores innovative ways to utilize technology and support older adults and their families in various settings, including home and hospice care. He also focuses on designing and evaluating personal health systems that produce patient-generated data including “smart home” solutions for aging. He is a Member of the National Academy of Medicine, a Fellow of the American College of Medical Informatics, the Gerontological Society of America, and the International Academy of Health Sciences Informatics. He has conducted numerous federally funded studies, and his work has been funded consistently over the years both by the National Institutes of Health (NIH) and the National Science Foundation (NSF). He directs the Penn Artificial Intelligence and Technology Collaboratory for Healthy Aging and is co-director of the Penn Community Collaboratory for Co-Creation.

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About Presentation

Title: Exploring the role of AI in Fall Prevention for Older Adults with Mild Cognitive Impairment

 

Fall prevention is critical for older adult populations. Cognitive impairment and housing conditions are both leading risk factors for falls. We developed an AI-based fall risk calculation and fall prevention intervention called Sense4Safety based on the use of depth sensors, machine learning and tailored exercise and educational modules specifically for community dwelling older adults with mild cognitive impairment who are socially vulnerable. We demonstrate the potential of AI to enhance traditional models of care and even introduce new ways for prevention and wellness. We present findings on the performance of the AI-mediated fall risk assessment and how it compares to human clinical expert assessment. Finally, we will discuss practical and ethical implications of the use of AI in gerontology.​