Machine assessment of neonatal facial expressions of acute pain

被引：64

作者：

Brahnam, Sheryl ^{[1
]}

Chuang, Chao-Fa

Sexton, Randall S.

Shih, Frank Y.

机构：

[1] SW Missouri State Univ, Springfield, MO 65804 USA

[2] New Jersey Inst Technol, Coll Comp Sci, Comp Vis Lab, Newark, NJ 07102 USA

来源：

DECISION SUPPORT SYSTEMS | 2007年 / 43卷 / 04期

关键词：

neonate pain recognition; medical face classification; support vector machines; linear discriminant analysis; principal component analysis; neural network simultaneous optimization algorithm;

D O I：

10.1016/j.dss.2006.02.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 18-72h) 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. (C) 2006 Elsevier B.V. All rights reserved.

引用

页码：1242 / 1254

页数：13

共 66 条

[1] ASSESSING DISTRESS IN PEDIATRIC INTENSIVE-CARE ENVIRONMENTS - THE COMFORT SCALE [J].