A robust neonatal facial pain cues classification

Link to publisher's homepage at http://www.ttp.net/

Saved in:
Bibliographic Details
Main Authors: Muhammad Naufal, Mansor, Mohd Nazri, Rejab
Other Authors: apairia@yahoo.com
Format: Article
Language:English
Published: Trans Tech Publications 2014
Subjects:
PCA
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33461
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-33461
record_format dspace
spelling my.unimap-334612014-04-07T04:44:41Z A robust neonatal facial pain cues classification Muhammad Naufal, Mansor Mohd Nazri, Rejab apairia@yahoo.com nazri_554@yahoo.com FFNN Fuzzy k-NN Infant pain k-NN LDA classifier PCA Link to publisher's homepage at http://www.ttp.net/ Late of infant pain detection on the early stage may affect newborns growth. Regarding of this matter, different techniques have been proposed such as facial expressions, speech production variation, and physiological signals to detect the pain states of a person. For past 2 decades, the determination of pain state through images has been undergone substantial research and development. Various techniques are used in the literature to classify pain states on the basis of images. In this paper, a feature extraction method using Principal Component Analysis (PCA) was adopted for identifying the pain states of an infant. In this study images samples are taken from Classification of Pain Expressions (COPE) database. Fuzzy k-NN, k Nearest Neighbor (k-NN), Feed Forward Neural network (FFNN) and Linear Discriminant analysis (LDA) based classifier is used to test usefulness of suggested features. Experimental result shows that the suggested methods can be used to identify the pain states of an infant. 2014-04-07T04:44:41Z 2014-04-07T04:44:41Z 2014 Article Applied Mechanics and Materials, vol.475-476, 2014, pages 1110-1117 1662-7482 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33461 http://www.scientific.net/AMM.475-476.1110 10.4028/www.scientific.net/AMM.475-476.1110 en Trans Tech Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic FFNN
Fuzzy k-NN
Infant pain
k-NN
LDA classifier
PCA
spellingShingle FFNN
Fuzzy k-NN
Infant pain
k-NN
LDA classifier
PCA
Muhammad Naufal, Mansor
Mohd Nazri, Rejab
A robust neonatal facial pain cues classification
description Link to publisher's homepage at http://www.ttp.net/
author2 apairia@yahoo.com
author_facet apairia@yahoo.com
Muhammad Naufal, Mansor
Mohd Nazri, Rejab
format Article
author Muhammad Naufal, Mansor
Mohd Nazri, Rejab
author_sort Muhammad Naufal, Mansor
title A robust neonatal facial pain cues classification
title_short A robust neonatal facial pain cues classification
title_full A robust neonatal facial pain cues classification
title_fullStr A robust neonatal facial pain cues classification
title_full_unstemmed A robust neonatal facial pain cues classification
title_sort robust neonatal facial pain cues classification
publisher Trans Tech Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33461
_version_ 1643797190945013760
score 13.214268