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PCA- Based Feature Extraction and LDA algorithm for Preterm Birth Monitoring  

1 *Muhammad Naufal Mansor, 2 Sazali Yaacob, 3 Hariharan Muthusamy, 4 Shafriza Nisha
Basah, 5 Shahrul Hi-fi Syam bin Ahmad Jamil, 6 Mohd Lutfi Mohd Khidir, 7 Muhammad
Nazri Rejab, 8 Ku Mohd Yusri Ku Ibrahim, 9 Addzrull Hi-fi Syam bin Ahmad Jamil, 10
Jamaluddin Ahmad , 11 Ahmad Kadri Junoh
1,2,3,4,11 Intelligent Signal Processing Group (ISP), University Malaysia Perlis, no 70 &71,
Blok B, Jalan Kangar- Alor setar, 02000, Kangar, Perlis, Malaysia.,,,,,
5,6,7,8,9 Fakulti Kejuruteraan Elekterik, Politeknik Tuanku Syed Sirajuddin, Km. 25, Lebuhraya
Kuala Perlis Changlun, Ulu Pauh, 02600, Arau, Perlis.,,,,,
10Pediatric Department, Hospital Tuanku Fauziah, Jalan Kolam,01000, Kangar,

Abstract .Most pregnancies last around 40 weeks. Babies born between 37 and 42 completed weeks of pregnancy are called full term. Premature birth is a serious health problem. Premature babies are at increased risk for newborn health complications, such as breathing problems, and even death. Most premature babies require care in a newborn intensive care unit (NICU). A preemie usually needs frequent office care – to screen vision or hearing problems and assess baby development – involving multiple medical disciplines which require accurate coordination. Thus, we proposed a monitoring system to classify the behavior of a preemie using intelligent vision system. The focus is on predicting preemie behavior based on preemie motion, face and skin analysis. Our preliminary experimental results show a promising performance of the initial part of the system involving preemie face, skin detection and LDA algorithm.
Keywords : Preterm Birtt; Image Processing; PCA; LDA

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