This paper is in the following e-collection/theme issue:

Digital Pain Assessment and Management (164) Machine Learning (1465) New and Emerging Methods and Tools in Surgery and Anaesthesiology (41) Perioperative Software Tools for Clinicians (13) Postoperative Pain Management (28)

Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23920, first published .
Novel Analgesic Index for Postoperative Pain Assessment Based on a Photoplethysmographic Spectrogram and Convolutional Neural Network: Observational Study

Novel Analgesic Index for Postoperative Pain Assessment Based on a Photoplethysmographic Spectrogram and Convolutional Neural Network: Observational Study

Novel Analgesic Index for Postoperative Pain Assessment Based on a Photoplethysmographic Spectrogram and Convolutional Neural Network: Observational Study

Authors of this article:

Byung-Moon Choi1 Author Orcid Image ;   Ji Yeon Yim2 Author Orcid Image ;   Hangsik Shin2 Author Orcid Image ;   Gyujeong Noh1, 3 Author Orcid Image
Article Authors Cited by (9) Tweetations (2) Metrics

Byung-Moon Choi   1 * , MD, PhD ;   Ji Yeon Yim   2 * , BSc ;   Hangsik Shin   2 * , PhD ;   Gyujeong Noh   1, 3 , MD, PhD

1 Department of Anaesthesiology and Pain Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea

2 Department of Biomedical Engineering, Chonnam National University, Yeosu, Republic of Korea

3 Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Hangsik Shin, PhD
  • Department of Biomedical Engineering
  • Chonnam National University
  • 50 Daehak-ro
  • Yeosu, 59626
  • Republic of Korea
  • Phone: 82 1068998679
  • Email: hangsik.shin@jnu.ac.kr