Feasibility study of a robotic medication assistant for the elderly

  • Authors:
  • Priyesh Tiwari;Jim Warren;Karen Day;Bruce MacDonald;Chandimal Jayawardena;I. H. Kuo;Aleksandar Igic;Chandan Datta

  • Affiliations:
  • University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand

  • Venue:
  • AUIC '11 Proceedings of the Twelfth Australasian User Interface Conference - Volume 117
  • Year:
  • 2011

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Abstract

Management of complex medication regimens by older people poses a significant challenge wherein use of information technology could play a role in improving clinical efficacy and safety of treatment. The use of computing devices, however, presents a special challenge to older people given their physical and cognitive limitations. Robotic platforms show promise for extending the functionality of the user interface to make personalized interaction engaging and empowering, and for proactively reaching out to older users to support their healthcare delivery. We believe that a robot combining a touch screen and voice based interface could offer an effective platform to meet these requirements. This paper reports on a feasibility study of such a system for helping older people with their medications. We exposed 10 relatively independent residents of an aged care facility to our robot running a medication reminding application while they took their medications. The interaction was followed by a questionnaire and structured interview to elicit their opinions and feedback. We found the application to be well received as all users could successfully complete the session, and most subjects found it easy to use, appropriately designed and felt confident using it. A number of technical errors were uncovered, and the results suggest opportunities to refine the equipment and dialog design to provide a better robotic medication assistant.