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.
Micheal Milburn and William DeJong, Impairment Science, Inc. Anuj Pradhan and Shannon Roberts, UMass Amherst. The Druid app uses multiple divided attention tasks to assess cognitive-motor behaviors related to driving. This project aims to validate the Druid app for use by older adults aged 64-85 years.
Dave Keeley, Electronic Caregiver, Inc. Michael Busa, UMass Amherst. This research project will enhance Electronic Caregiver's Addison Care system with computer vision methods for evaluating functional strength, stability, and falls risk in older adults.