Anna Barnacka, MindMics Inc. This project will collect data for building and validating algorithms for analytics of vascular aging using Infrasonic Hemodynography with wearable earphones (the MindMics device).
Edward Jay Wang, UCSD. Given the prevalence of uncontrolled hypertension and additional challenges in the older adult population, it is essential that measurement of BP be done easily and accurately. This project will develop an ultra low cost approach to converting the billions of smartphone cameras, even the cheapest ones, into blood pressure monitors that can be used by older adults at home.
Amanda Paluch, UMass Amherst. Dae Hyun Kim, Hebrew SeniorLife. Rags Gupta, Butlr Technologies Inc. This project will develop a contactless in-home assessment tool for frailty using body heat sensing technology. The ceiling or wall-mounted heat sensors, developed by butlr Technologies, will measure real-time movement of free-living people without jeopardizing privacy.
Ipsit Vahia, McLean Hospital. Rachel Sava, McLean Hospital. Appropriate and personalized pharmacologic management of behavioral and psychologic symptoms in dementia (BPSD) is among the most complex clinical challenges in dementia care. This project will will pilot an AI-guided approach using Garmin wearable sensors that can generate real-time objective data from patients with Alzheimer’s Disease and other related dementias (ADRD) being treated for BPSD in McLean’s Geriatric Psychiatry Outpatient Program.
Jen Blankenship, VivoSense Inc. Michael Busa, UMass Amherst. The aim of this project is to develop and validate algorithms to capture measures of real-world walking behavior in patients with Alzheimer’s disease (AD). This project will provide critical validation evidence to support regulatory decision making.
Erik Larsen, Sonde Health. Brad Dickerson, Massachusetts General Hospital. Bonnie Wong, Massachusetts General Hospital. This project enrolls 50 subjects, age 55 and above, to participate in a longitudinal pilot study examining the potential to monitor mental status as a way to detect potential declines in cognitive functioning through a voice analysis (vocal biomarker) platform implemented on an existing smartphone app. The focus of this study is on feasibility in naturalistic environments (home) vs. controlled laboratory setting.