Hamed Tabkhi, Mona Azarbayjani, ForesightCares Inc. Sanjay Iyer, Memory & Movement Charlotte. The pilot project focused on developing and validating an AI-based visual assessment (AVA) app for at-home monitoring of motor function in older adults with Parkinson’s Disease (PD).
Gang Wang, University of Illinois at Urbana-Champaign. Roopa Foulger, OSF. This project will design, prototype, evaluate, and potentially deploy an AI-enabled voice agent to assist patients (especially older adults) to better recognize phishing messages and reduce cybersecurity risks during patient outreach and communications.
Edward Jay Wang, Billion Labs Inc. This project aims to establish accessible early screening of hypertension by democratizing BP monitoring. We aim to achieve this by converting the billions of smartphones into oscillometric BP monitors without hardware add-ons.
Inbal Billie Nahum-Shani, University of Michigan. Vivek Shetty, UCLA. Guy Shani, Michigan State University. Susan A. Murphy, Harvard University. This project seeks to develop a novel AI-powered digital tool to empower older adults with Alzheimer's disease and related dementias (AD/ADRD) to engage in oral self-care in at-home settings.
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.