Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study.

Journal: JMIR mHealth and uHealth
Published Date: May 5, 2021

Abstract

BACKGROUND: Accurate, objective pain assessment is required in the health care domain and clinical settings for appropriate pain management. Automated, objective pain detection from physiological data in patients provides valuable information to hospital staff and caregivers to better manage pain, particularly for patients who are unable to self-report. Galvanic skin response (GSR) is one of the physiologic signals that refers to the changes in sweat gland activity, which can identify features of emotional states and anxiety induced by varying pain levels. This study used different statistical features extracted from GSR data collected from postoperative patients to detect their pain intensity. To the best of our knowledge, this is the first work building pain models using postoperative adult patients instead of healthy subjects.

Authors

  • Seyed Amir Hossein Aqajari
    Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States.
  • Rui Cao
    Department of Cardiology of Lu'an People's Hospital, Lu'an Hospital of Anhui Medical University, Lu'an, China.
  • Emad Kasaeyan Naeini
    Department of Computer Science, University of California, Irvine, Irvine, CA, United States.
  • Michael-David Calderon
    Department of Anesthesiology & Perioperative Care, University of California Irvine, 101 The City Drive South, Orange, CA, 92868, USA.
  • Kai Zheng
    University of California, Irvine, Irvine, CA, USA.
  • Nikil Dutt
    Department of Computer Science, University of California Irvine, Irvine, CA, USA; Department of Cognitive Sciences, University of California Irvine, Irvine, CA, USA.
  • Pasi Liljeberg
    Department of Future Technologies, University of Turku, Turku, Finland.
  • Sanna Salanterä
    Nursing Science, University of Turku, and Turku University Hospital, Turku, Finland.
  • Ariana M Nelson
    Department of Anesthesiology and Perioperative Care, University of California, Irvine, Irvine, CA, United States.
  • Amir M Rahmani
    Department of Computer Science, University of California Irvine, Irvine, USA.

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