I know mom is ok: Next Generation Precision Health Care for Older Adults
 

Artificial intelligence (AI) and machine learning news uses have grown exponentially over the past year. News stories have exploded with cautionary tales. But what if AI could be harnessed for good? In her talk, Dr. Rachel Proffitt will detail advances in machine and deep learning paired with in-home sensors to support older adults living in the community. She will include findings from recent and ongoing federally funded research studies and discuss the implications for supporting rural health care and aging-in-place.

About the NextGen Precision Health Discovery Series
 

The NextGen Precision Health Discovery Series provides learning opportunities for UM System faculty and staff across disciplines, the statewide community and our other partners to learn about the scope of precision health research and identify potential collaborative opportunities. The series consists of monthly lectures geared toward a broad multidisciplinary audience so all can participate and appreciate the spectrum of precision health efforts. 

Dr. Rachel Proffitt is Associate Professor in the Department of Occupational Therapy, College of Health Sciences, University of Missouri. Her research focuses on developing, testing, and implementing virtual reality-based interventions for adults and older adults post-stroke. Dr. Proffitt has extensive experience working in an interdisciplinary setting with computer scientists and engineers and was previously the director of the Game Based Rehab Lab at the Institute for Creative Technologies at the University of Southern California (USC). She has completed a T32 postdoctoral fellowship with an emphasis in rehabilitation clinical trials as well as a KL2 Career Development Award. She is currently translating effective interventions, such as LSVT®BIG, for use with the stroke population and pairing telehealth applications for remote delivery in rural areas. Dr. Proffitt is PI of an NIH R21 to develop a new algorithm for activity recognition and assessment in the natural home environment for individuals post-stroke and the PI of an NIH R01 to evaluate a sensor system in the homes of rural community-dwelling older adults.