AAAI Publications, Workshops at the Thirtieth AAAI Conference on Artificial Intelligence

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A Prototype Intelligent Assistant to Help Dysphagia Patients Eat Safely At Home
Michael Freed, Brian Burns, Aaron Heller, Daniel Sanchez, Sharon Beaumont-Bowman

Last modified: 2016-03-29

Abstract


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 could effectively monitor chin tuck adherence, and suggest the feasibility of a more general assistant that encourages adherence to a wide range of safe eating strategies.

Keywords


machine vision; intelligent personal assistant; dysphagia; m

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