Wenyao Xu, Auspex Medix. Wei Sun, University at Buffalo. This project is to investigate an AI-powered, smartphone-based hearing screening tool that uses non-volitional pupillary responses to objectively assess hearing functions and loss.
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.
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.
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).
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.
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.
Archna Bhatia, Institute for Human & Machine Cognition, George Sperling, UCI. This project aims to develop an Intelligent Cognitive Assistant that provides real-time word retrieval support as well as personalized training to enhance word retrieval for individuals with mild cognitive impairment and Alzheimer’s Disease and Related Dementias.