Feasibility of a Real-Time Clinical Augmented Reality and Artificial Intelligence Framework for Pain Detection and Localization From the Brain.

Journal: Journal of medical Internet research
Published Date: Jun 28, 2019

Abstract

BACKGROUND: For many years, clinicians have been seeking for objective pain assessment solutions via neuroimaging techniques, focusing on the brain to detect human pain. Unfortunately, most of those techniques are not applicable in the clinical environment or lack accuracy.

Authors

  • Xiao-Su Hu
    Headache & Orofacial Pain Effort Lab, Biologic & Materials Sciences Department, School of Dentistry, University of Michigan, Ann Arbor, MI, United States.
  • Thiago D Nascimento
    Headache & Orofacial Pain Effort Lab, Biologic & Materials Sciences Department, School of Dentistry, University of Michigan, Ann Arbor, MI, United States.
  • Mary C Bender
    Headache & Orofacial Pain Effort Lab, Biologic & Materials Sciences Department, School of Dentistry, University of Michigan, Ann Arbor, MI, United States.
  • Theodore Hall
    3D Lab, Digital Media Commons, University of Michigan, Ann Arbor, MI, United States.
  • Sean Petty
    3D Lab, Digital Media Commons, University of Michigan, Ann Arbor, MI, United States.
  • Stephanie O'Malley
    3D Lab, Digital Media Commons, University of Michigan, Ann Arbor, MI, United States.
  • Roger P Ellwood
    Clinical Method Development, Colgate Palmolive, Piscataway, NJ, United States.
  • Niko Kaciroti
    Headache & Orofacial Pain Effort Lab, Biologic & Materials Sciences Department, School of Dentistry, University of Michigan, Ann Arbor, MI, United States.
  • Eric Maslowski
    Moxytech Inc, Ann Arbor, MI, United States.
  • Alexandre F DaSilva
    Headache & Orofacial Pain Effort Lab, Biologic & Materials Sciences Department, School of Dentistry, University of Michigan, Ann Arbor, MI, United States.

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