Walter Boot and FSU research team win $2.9-million award from National Institute on Aging
The National Institute on Aging has given an R01 grant to ISL Faculty Affiliates Walter Boot, Ph.D., the principal investigator, and Shayok Chakraborty, Ph.D., the co-PI, along with an interdisciplinary team of FSU researchers, for their project: The Adherence Promotion with Person-centered Technology (APPT) Project: Promoting Adherence to Enhance the Early Detection and Treatment of Cognitive Decline.
The total award is for $2.9 million.
The Institute for Successful Longevity served as a crucial resource for the formation of this interdisciplinary team. In addition to Dr. Boot of the Department of Psychology and Dr. Chakraborty of the Department of Computer Science, the team includes ISL affiliates Zhe He, Ph.D., of the School of Information; Dawn Carr, Ph.D., of the Department of Sociology; and Antonio Terracciano, Ph.D., of the College of Medicine, as well as ISL Director Dr. Neil Charness. Dr. Mia Lustria of the School of Information is also a team member.
The aims of the project are to promote early detection and treatment of age-related cognitive decline and dementia. The significance of the project is highlighted by Boot, who said, "As the population in the United States and around the world ages, it will be important to understand ways to detect cognitive change as soon as possible so individuals experiencing these changes can be treated and supported. This project will help develop effective methods through which cognitive changes can be monitored over time in someone's own home, using technology."
Although mobile cognitive assessments and training are available, Boot said, these are only part of the solution. People need to engage with assessment and training over a long period of time for benefits to be observed. This project will develop Artificial Intelligence (AI)-based reminder systems to help ensure long-term engagement with home-based cognitive assessment and cognitive training protocols. AI reminder systems will learn about the user and adapt based on their history and their preferences.
“This project involves fundamental AI challenges such as learning from multiple sources of heterogeneous data, learning from data on-the-fly in real-time, as well as learning in the presence of weak supervision and noisy annotations,” said Chakraborty. “This research will result in the development of next generation AI-based assistive aids for the elderly, with the potential to improve their health and well-being, as well as promote independent living.”
The ability to detect that someone is on the cusp of cognitive decline has large implications for how dementia is studied. Treatments and interventions can be tested before large changes in brain structure and function that may be hard to reverse have occurred.