Jennifer Flexman, Moneta Health. Michael Busa, UMass Amherst. This project will develop AI algorithms used by Moneta™ digital therapy assistant to monitor the speech of individuals with mild cognitive impairment and early dementia during cognitive rehabilitation therapy.
Xian Du, Joohyun Chung, UMass Amherst. Shishir Prasad, BD. In this project, we will develop the approach for the continuous monitoring of long-term care (LTC) resident’s behavioral and physiological signals over extended durations using cameras and wearable sensors.
Ipsit Vahia, Rachel Sava, McLean Hospital. Joseph Chung, Rippl. This project seeks to identify the specific domains of caregiver support that may be best served by AI over geriatric care managers, and to develop an ethical framework for the interaction between caregivers and large language models.
https://www.youtube.com/watch?v=tVFTmTnYb4M Speaker: Joseph E. Gaugler, PhD Robert L. Kane Endowed Chair in Long-Term Care & Aging in School of Public Health Distinguished McKnight University Professor Director of the Center for Healthy Aging and Innovation Director of the national BOLD Public Health Center of Excellence on Dementia Caregiving University of Minnesota Editor-in-Chief of The Gerontologist Abstract: Various technologies are now available that purport to support families, friends, and other unpaid individuals who care for older adults living with dementia. Although such technologies may hold promise, it remains less clear whether these technologies are truly effective or aligned with the heterogeneity of dementia care, particularly dementia care that takes place in the community. This presentation will summarize recent findings and identify opportunities to utilize technology to advance the science and support of dementia care. Aligning Technology…
Joyita Dutta, UMass Amherst. This project will develop AI techniques for at-home sleep staging in seniors using multimodal data from EEG headband and smartwatch devices.
Honghuang Lin, UMass Chan Medical School. This study will leverage a large collection of physical activity and cognitive assessment data to derive novel digital phenotypes from commercially available wearable devices.
Quan Zhang, Massachusetts General Hospital. This project will create an adapted version of NINscan, a Near-Infrared Neuromonitoring Device, with the goal of enabling older adults and AD patients to collect high quality brain and physiological data at home.