University of Oulu

Zebarjadi, N. and Alikhani, I. (2017). Static and Dynamic Approaches for Pain Intensity Estimation using Facial Expressions.In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017) ISBN 978-989-758-213-4, pages 291-296. DOI: 10.5220/0006141502910296

Static and dynamic approaches for pain intensity estimation using facial expressions

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Author: Zebarjadi, Niloufar1; Alikhani, Iman1
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019082124951
Language: English
Published: SCITEPRESS Science And Technology Publications, 2017
Publish Date: 2019-08-21
Description:

Abstract

Self-report is the most conventional means of pain intensity assessment in clinical environments. But, it is not an accurate metric or not even possible to measure in many circumstances, e.g. intensive care units. Continuous and automatic pain level evaluation is an advantageous solution to overcome this issue. In this paper, we aim to map facial expressions to pain intensity levels. We extract well-known static (local binary pattern(LBP) and dense scale-invariant feature transform (DSIFT)) and dynamic (local binary patterns on three orthogonal planes (LBP-TOP) and three dimensional scale-invariant feature transform (3D-SIFT)) facial feature descriptors and employ the linear regression method to label a number between zero (no pain) to five (strong pain) to each testing sequence. We have evaluated our methods on the publicly available UNBC-McMaster shoulder pain expression archive database and achieved average mean square error (MSE) of 1.53 and Pearson correlation coefficient (PCC) o f 0.79 using leave-one-subject-out cross validation. Acquired results prove the superiority of dynamic facial features compared to the static ones in pain intensity determination applications.

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ISBN: 978-989-758-213-4
Volume: 5
Pages: 291 - 296
DOI: 10.5220/0006141502910296
OADOI: https://oadoi.org/10.5220/0006141502910296
Host publication: Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies, Vol 5: HealthINF
Host publication editor: van den Broek, Egon L.
Fred, Ana
Gamboa, Hugo
Vaz, Mário
Conference: International Joint Conference on Biomedical Engineering Systems and Technologies
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
217 Medical engineering
Subjects:
LBP
Copyright information: © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.