A Preliminary Usability Evaluation of an Artificial Intelligence-Based, Motion-Detecting Wearable Device: The Geriatric Functional Assessment System.

Journal: The journals of gerontology. Series A, Biological sciences and medical sciences
PMID: 40037593

Abstract

BACKGROUND: Physical function is a key determinant of independence among older adults. Yet, there are barriers to assessing physical function in clinic. We developed a wearable geriatric functional assessment system (GFAS) that quickly and effortlessly evaluates physical function.

Authors

  • John A Batsis
    The Dartmouth Institute for Health Policy, Dartmouth, Lebanon, NH, United States.
  • Rishank Singh
    Department of Computer Science, University of Massachusetts Boston, Boston, Massachusetts, USA.
  • Jennifer Poole
    Division of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
  • Paige Bramblett
    Division of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
  • Danae Gross
    Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Meredith Gilliam
    Division of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
  • Chaterlee Pamintuan
    Division of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
  • Beckham Nora
    Division of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
  • David H Lynch
    Division of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
  • Xiaohui Liang
    Department of Computer Science, University of Massachusetts, Boston, MA, United States.

Keywords

External Resources

Popular Topics
Recent Journals