Title
Introduction to neonatal facial pain detection using common and advanced face classification techniques
Abstract
Assessing pain in neonates is a challenging problem. Neonates cannot describe their pain experiences but must rely exclusively on the judgments of others. Studies demonstrate, however, that proper diagnosis of pain is impeded by observer bias. It has therefore been recommended that neonatal pain assessment instruments include evaluations that have bypassed an observer. In this article, we describe the Infant COPE project and our work using face classification to detect pain in a neonate's facial displays. We begin by providing an introduction to face classification that includes an outline of some common and advanced algorithms.We then describe a small database we designed specifically to investigate classifier performance in this problem domain. This is followed by a summary of the experiments we have performed to date, including some preliminary results of current work. We believe these results indicate that the application of face classification to the problem of neonatal pain assessment is a promising area of investigation.
Department(s)
Information Technology and Cybersecurity
Document Type
Article
DOI
https://doi.org/10.1007/978-3-540-47527-9_9
Publication Date
5-8-2007
Recommended Citation
Brahnam, Sheryl, Loris Nanni, and Randall Sexton. "Introduction to neonatal facial pain detection using common and advanced face classification techniques." In Advanced Computational Intelligence Paradigms in Healthcare–1, pp. 225-253. Springer, Berlin, Heidelberg, 2007.
Journal Title
Studies in Computational Intelligence
