Jennifer Rae Myers, Chelsea S. Brown, Musical Health Technologies. This pilot project focused on developing an equitable machine learning (ML)-based music intervention for older adults at risk for Alzheimer’s disease. The study progressed through two phases, beginning with IRB approvals and participant recruitment in mid-2024.
Ehsan Adeli, Victor W. Henderson, Stanford University. The proposed project aims to design a mobile app that not only instructs and records individuals performing Short Physical Performance Battery (SPPB) tests but also uses these data for predictive analysis to monitor and quantify the risk of cognitive impairment over time, utilizing video data analyzed for motor-cognitive relationships.
G. Antonio Sosa-Pascual, REOFTech. Michael Busa, UMass Amherst. This project aims to collect data from wearables and smart home sensors to determine the state, rate, and direction of change in dementia patient agitation and caregiver well-being.
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.
The team including Drs. Vahia and Sava and previous a2 Pilot awardee, Rippl (formerly known as Kinto) received GY3 pilot award to explore the use of LLMs to support caregivers of individuals with dementia. Source: https://massaitc.org/2024/04/18/creating-a-framework-for-large-language-models-for-caregiver-support-in-dementia/
Ipsit Vahia, Rachel Sava, McLean Hospital. Joseph Chung, Rippl. The CAREALL pilot project explored the use of large language models (LLMs) to support caregivers of individuals with dementia.