SVM classification of neonatal facial images of pain

Sheryl Brahnam, Chao Fa Chuang, Frank Y. Shih, Melinda R. Slack

Research output: Chapter in Book/Report/Conference proceedingConference contribution

35 Scopus citations


This paper reports experiments that explore performance differences in two previous studies that investigated SVM classification of neonatal pain expressions using the Infant COPE database. This database contains 204 photographs of 26 neonates (age 18-36 hours) experiencing the pain of heel lancing and three nonpain Stressors. In our first study, we reported experiments where representative expressions of all subjects were included in the training and testing sets, an experimental protocol suitable for intensive care situations. A second study used an experimental protocol more suitable for short-term stays: the SVMs were trained on one sample and then evaluated on an unknown sample. Whereas SVM with polynomial kernel of degree 3 obtained the best classification score (88.00%) using the first evaluation protocol, SVM with a linear kernel obtained the best classification score (82.35%) using the second protocol. However, experiments reported here indicate no significant difference in performance between linear and nonlinear kernels.

Original languageEnglish (US)
Title of host publicationFuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers
Number of pages8
StatePublished - 2006
Event6th International Workshop - Fuzzy Logic and Applications - Crema, Italy
Duration: Sep 15 2005Sep 17 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3849 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other6th International Workshop - Fuzzy Logic and Applications

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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