Fast infant pain detection method

Link to publisher's homepage at http://ieeexplore.ieee.org

Saved in:
Bibliographic Details
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:
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/26562
Tags: Add Tag
No Tags, Be the first to tag this record!
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
score 13.222552