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 (ADRD) to engage in oral self-care in at-home settings. This Dyadic Digital Coach (DDC) will leverage the untapped potential of dyadic relationships between older adults and their primary caregivers.
Jennifer Rae Myers, Chelsea S. Brown, Musical Health Technologies. This project will use machine learning to enhance cultural relevance and usability of a therapeutic mHealth app (SingFit) for the purpose of improving cognitive and emotional health in at-risk older adults.
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. Analyzing the strength, directionality, and temporal relationship between the classifiers from each specific dyad member will allow our platform to provide novel insights and actionable intelligence for both the dyad and their clinical care providers.
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.