Fast infant pain detection method

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Main Authors:	Muhammad Naufal, Mansor, Syahryull Hi-Fi Syam, Ahmad Jamil, Ahmad Kadri, Junoh, Muhammad Nazri, Rejab, Addzrull Hi-Fi Syam, Ahmad Jamil, Jamaluddin, Ahmad
Other Authors:	apairia@yahoo.com
Format:	Working Paper
Language:	English
Published:	Institute of Electrical and Electronics Engineers (IEEE) 2013
Subjects:	Detection of facial changes NICU patient Support Vector Machine classifier
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/26562
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Institution:	Universiti Malaysia Perlis
Language:	English

id	my.unimap-26562
record_format	dspace
spelling	my.unimap-265622013-07-10T07:47:15Z Fast infant pain detection method Muhammad Naufal, Mansor Syahryull Hi-Fi Syam, Ahmad Jamil Ahmad Kadri, Junoh Muhammad Nazri, Rejab Addzrull Hi-Fi Syam, Ahmad Jamil Jamaluddin, Ahmad apairia@yahoo.com syahrull30@yahoo.com kadri@unimap.edu.my nazri_554@yahoo.com azrulhifisyam@yahoo.com drjamaluddin@pls.moh.gov.my Detection of facial changes NICU patient Support Vector Machine classifier Link to publisher's homepage at http://ieeexplore.ieee.org within this paper, pain detection is exposed and reviewed for detecting facial changes of patient in a hospital in Neonatal Intensive Care Unit (NICU). The system propesed three stage. The first stage implements Haar Cascade detection to detect the infant face. Secondly, PCA was employed for feature extraction. The third module extracts the PCA features of faces by measuring certain dimensions of pain and no pain regions with Support Vector Machine classifier. From 300 samples of face images, it is found that the identification rate of reaches 93.18%. 2013-07-10T07:47:15Z 2013-07-10T07:47:15Z 2012-07-03 Working Paper p. 918-921 978-146730478-8 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6271350 http://hdl.handle.net/123456789/26562 en Proceedings of the International Conference on Computer and Communication Engineering (ICCCE 2012) Institute of Electrical and Electronics Engineers (IEEE)
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	Detection of facial changes NICU patient Support Vector Machine classifier
spellingShingle	Detection of facial changes NICU patient Support Vector Machine classifier Muhammad Naufal, Mansor Syahryull Hi-Fi Syam, Ahmad Jamil Ahmad Kadri, Junoh Muhammad Nazri, Rejab Addzrull Hi-Fi Syam, Ahmad Jamil Jamaluddin, Ahmad Fast infant pain detection method
description	Link to publisher's homepage at http://ieeexplore.ieee.org
author2	apairia@yahoo.com
author_facet	apairia@yahoo.com Muhammad Naufal, Mansor Syahryull Hi-Fi Syam, Ahmad Jamil Ahmad Kadri, Junoh Muhammad Nazri, Rejab Addzrull Hi-Fi Syam, Ahmad Jamil Jamaluddin, Ahmad
format	Working Paper
author	Muhammad Naufal, Mansor Syahryull Hi-Fi Syam, Ahmad Jamil Ahmad Kadri, Junoh Muhammad Nazri, Rejab Addzrull Hi-Fi Syam, Ahmad Jamil Jamaluddin, Ahmad
author_sort	Muhammad Naufal, Mansor
title	Fast infant pain detection method
title_short	Fast infant pain detection method
title_full	Fast infant pain detection method
title_fullStr	Fast infant pain detection method
title_full_unstemmed	Fast infant pain detection method
title_sort	fast infant pain detection method
publisher	Institute of Electrical and Electronics Engineers (IEEE)
publishDate	2013
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/26562
_version_	1643794985531736064

Fast infant pain detection method

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