John Ralston, Neursantys Inc. VP Nguyen, UMass Amherst This project will develop ML-driven methods to adapt EVS stimulus parameters to each patient’s unique sensory and motor impairment profile to increase the effectiveness of NEURVESTA’s current treatment protocol.
Hamed Tabkhi, Mona Azarbayjani, ForesightCares Inc. Sanjay Iyer, Memory & Movement Charlotte. The project aims to conduct a feasibility study on utilizing an AI-based visual assessment application to assess the balance, gait, and hand movements of older adults with Parkinson's disease (PD) within their home environments, focusing on underserved communities in Charlotte. The ultimate objective is to eliminate barriers to digital health equity and enhance access to marginalized older adults with 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 (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.