Machine assessment of neonatal facial expressions of acute pain
Document Type
Article
Publication Date
8-1-2007
Abstract
We propose that a machine assessment system of neonatal expressions of pain be developed to assist clinicians in diagnosing pain. The facial expressions of 26 neonates (age 18-72 h) were photographed experiencing the acute pain of a heel lance and three nonpain stressors. Four algorithms were evaluated on out-of-sample observations: PCA, LDA, SVMs and NNSOA. NNSOA provided the best classification rate of pain versus nonpain (90.20%), followed by SVM with linear kernel (82.35%). We believe these results indicate a high potential for developing a decision support system for diagnosing neonatal pain from images of neonatal facial displays. © 2006 Elsevier B.V. All rights reserved.
Identifier
34547666978 (Scopus)
Publication Title
Decision Support Systems
External Full Text Location
https://doi.org/10.1016/j.dss.2006.02.004
ISSN
01679236
First Page
1242
Last Page
1254
Issue
4
Volume
43
Grant
1015-22-2181
Fund Ref
Missouri State University
Recommended Citation
Brahnam, Sheryl; Chuang, Chao Fa; Sexton, Randall S.; and Shih, Frank Y., "Machine assessment of neonatal facial expressions of acute pain" (2007). Faculty Publications. 13370.
https://digitalcommons.njit.edu/fac_pubs/13370
