Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study.

Journal: JMIR mHealth and uHealth
Published Date: Aug 7, 2020

Abstract

BACKGROUND: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process.

Authors

  • Curtis Lee Petersen
    The Dartmouth Institute for Health Policy, Dartmouth, Hanover, NH, United States.
  • Ryan Halter
    Thayer School of Engineering, Dartmouth, Hanover, NH, United States.
  • David Kotz
    Computer Science, Dartmouth, Hanover, NH, United States.
  • Lorie Loeb
    Computer Science, Dartmouth, Hanover, NH, United States.
  • Summer Cook
    Department of Kinesiology, University of New Hampshire, Durham, NH, United States.
  • Dawna Pidgeon
    Department of Physical Medicine and Rehabilitation, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States.
  • Brock C Christensen
    Department of Epidemiology, Lebanon, USA. Brock.C.Christensen@dartmouth.edu.
  • John A Batsis
    The Dartmouth Institute for Health Policy, Dartmouth, Lebanon, NH, United States.

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