Mark Eldaief, Massachusetts General Hospital. This project will establish a “technology-ready cohort” of individuals with Alzheimer’s Disease and related dementias to support the evaluation of digital assessments relevant to ADRD patients and their caregivers.
Rebecca Spencer, UMass Amherst. The pilot project aimed to validate the accuracy and usability of commercial sleep tracking devices in older adults, including those with Alzheimer’s disease (AD), related dementias (ADRD), or mild cognitive impairment (MCI).
Richard Watkins, Livindi. The Livindi pilot project aimed to develop and test a technology platform that detects distress-related events—especially falls—using audio recognition, motion sensors, and machine learning. Participants received pre-configured kits with tablets and sensors, and the system was designed to operate entirely on-device to ensure privacy.
Amar Basu, Wayne State University, Michael Busa, UMass Amherst. This project will evaluate TRACE, a novel wearable sensor for monitoring orthostatic vital signs continuously at home, whenever an individual stands up.
Jennifer Williams, Stanford University. This project will develop and test an approach to monitoring older adults with chronic obstructive pulmonary disease in the home using an unobtrusive metric derived from acoustic features collected during normal cell phone use.
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.
Jennifer Stamps and Kyle Rand, Rendever, Inc. This pilot study will evaluate the utility of RendeverFit™, a VR fitness platform, in terms of its acceptance by and relevance to older adults, as well as collect data to support the construction of machine learning models.