Title :
Fast infant pain detection method
Author :
Mansor, Muhammad Naufal ; Rejab, Mohd Nazri ; Jamil, Syahryull Hi-Fi Syam Ahmad ; Jamil, Addzrull Hi-Fi Syam Ahmad ; Junoh, A.K. ; Ahmad, Jawad
Author_Institution :
Intell. Signal Process. Group, Univ. Malaysia Perils, Kangar, Malaysia
Abstract :
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%.
Keywords :
Haar transforms; face recognition; hospitals; image classification; medical image processing; patient diagnosis; principal component analysis; support vector machines; Haar cascade detection; NICU; Neonatal Intensive Care Unit; PCA features; face image sampling; facial changes detection; fast infant pain detection method; feature extraction; hospital; infant face detection; support vector machine classifier; Face; Face detection; Feature extraction; Pain; Pediatrics; Principal component analysis; Support vector machines; Detection of facial changes; NICU patient; Support Vector Machine classifier;
Conference_Titel :
Computer and Communication Engineering (ICCCE), 2012 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-0478-8
DOI :
10.1109/ICCCE.2012.6271350
