Marziye Eshghi, MGH Institute of Health Professions This project will leverage AI-driven analysis of remotely collected speech data to detect early signs of Alzheimer’s disease (AD) by linking speech acoustic and kinematic features to AD molecular pathologies.
Tim K. Mackey, S-3 Research LLC, Joshua Yang, California State University, Fullerton. This project will aim to develop TrialChat, an AI-powered chatbot and clinical trial navigator designed to increase participation in Alzheimer’s disease and related dementias (ADRD) clinical trials by providing tailored education, personalized trial matching, and recruitment support for older adults and caregivers.
Raeanne C Moore, UCSD, Yeonsu Song, UCLA. This project will develop and pilot machine learning algorithms to passively monitor cognitive fluctuations among family caregivers of persons living with dementia by analyzing their smartphone typing patterns and speech.
Rhoda Au, Boston University, Laura McIntosh, EmPowerYu. This project will use in-home multimodal sensors to detect changes in daily life activity patterns that indicate fluctuations in cognitive status.
Jeremy Linsley, Operant BioPharma This project will use a proprietary robotics and artificial intelligence to identify targets and clinically-tested drugs that could be repurposed for Alzheimer's disease by blocking the harmful interaction between Tau and Amyloid Precursor proteins.
Chaitanya Gupta, ProbiusDX Inc., Steven Arnold, Massachusetts General Hospital. This project will use Probius QES, a novel technology that measure molecular vibrations in blood plasma samples, to identify and differentiate healthy aging vs Alzheimer’s Disease progression in a well characterized cohort of 1000+ individuals from MassGen.
About the Product: AVA is an AI-powered app for routine fall risk assessment. No external hardware, no stored videos - just fast, reliable insights to support safer aging at home! ForesightCares presents AVA, an AI-driven video-based mobile application designed for non-invasive, real-time fall risk assessment of older adults. AVA leverages advanced AI models to analyze mobility patterns using only iPads' built-in cameras, eliminating the need for wearable sensors or video storage. Designed for caregivers, family members, and staff in Independent Living communities, AVA offers a fast, five-minute assessment that ensures full privacy by performing all processing on-device. Its user-friendly interface, affordability, and broad device compatibility make it an essential tool for proactive fall risk evaluation. While AVA does not replace professional medical assessments, it empowers caregivers with objective insights to support safer aging. Source: AVA…