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Prospective Study Evaluating a Pain Assessment Tool in a Postoperative Environment: Protocol for Algorithm Testing

Emad Kasaeyan Naeini1, Mingzhe Jiang2, Elise Syrjälä2

  • 1Department of Computer Science, University of California, Irvine, Irvine, CA, United States.

JMIR Research Protocols
|July 2, 2020
PubMed
Summary

This study develops an objective pain assessment tool using wearable sensors to measure physiological and behavioral indicators. The tool aims to improve pain management for patients with mild to moderate pain.

Keywords:
acute painhealth monitoringmachine learningmultimodal biosignalspain measurementpain, postoperativewearable electronic devices

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Area of Science:

  • Biomedical Engineering
  • Pain Medicine
  • Wearable Technology

Background:

  • Accurate pain assessment is crucial for effective pain management, yet self-reporting has limitations, especially in non-communicative patients.
  • Existing objective methods using physiological signals (ECG, EMG, PPG, EDA) are often unreliable due to confounding factors.
  • Behavioral indicators, such as facial expressions, are emerging as promising objective pain assessment markers.

Purpose of the Study:

  • To advance the development and research of a novel, objective pain assessment tool.
  • To utilize wearable technologies for collecting multimodal physiological and behavioral data.
  • To assess mild to moderate pain in communicative patients post-surgery.

Main Methods:

  • This study is the second phase of a larger research project focusing on multimodal signal acquisition.
  • Utilized state-of-the-art sensors to measure facial electromyography (fEMG), electrocardiography (ECG), photoplethysmography (PPG), and electrodermal activity (EDA).
  • Developed and refined a smart pain assessment tool with modern wearable sensors, devices, and algorithms for testing in a recovery room setting.

Main Results:

  • Institutional Review Board approval was obtained for this phase of the study.
  • The pain assessment tool is expected to be developed and available for further research by early 2021.
  • Preliminary results were anticipated for publication in fall 2020.

Conclusions:

  • This research contributes to the development of an objective pain assessment tool.
  • The tool aims to provide continuous monitoring for patients experiencing mild to moderate pain.
  • Further research will validate the efficacy of this multimodal approach in clinical settings.