Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

A Virtual Assistant to Help Dysphagia Patients Eat Safely at Home / 4244
Michael Freed, Brian Burns, Aaron Heller, Daniel Sanchez, Sharon Beaumont-Bowman

For millions of people with swallowing disorders, preventing potentially deadly aspiration pneumonia requires following prescribed safe eating strategies. But adherence is poor, and caregivers' ability to encourage adherence is limited by the onerous and socially aversive need to monitoring another's eating. We have developed an early prototype for an intelligent assistant that monitors adherence and provides feedback to the patient, and tested monitoring precision with healthy subjects for one strategy called a chin tuck. Results indicate that adaptations of current generation machine vision and personal assistant technologies can effectively monitor chin tuck adherence, and suggest feasibility of a more general assistant that encourages adherence to a range of safe eating strategies.