Clinical infant pain trial based on k-NN algorithm

Author

Naufal Mansor, M. ; Hi-Fi Syam, S. ; Nazri Rejab, M. ; Hi-Fi Syam B, Addzrull

Author_Institution

Sch. of Mechatron. Eng., Univ. Malaysia Perlis, Kangar, Malaysia

Volume

2

fYear

2012

Firstpage

371

Lastpage

373

Abstract

This paper presents a vision-based infant-pain monitoring system that adopts an infant behavior analysis approach to detect infant injuries. In our study, the system first pre-processes the input sequence to filter out the noise and reduce the effects of lights and shadows. Then, the infant´s faces are detected from the input frames and feature extraction was done with SVD and FFT. A k-NN classifier was employed to describe pain over time. It is found that the identification rate of reaches 83.12%.

Keywords

emotion recognition; face recognition; fast Fourier transforms; feature extraction; filtering theory; image classification; image denoising; injuries; medical image processing; paediatrics; patient monitoring; singular value decomposition; vision; FFT; SVD; clinical infant pain trial; feature extraction; infant behavior analysis approach; infant face detection; infant injuries; k-NN algorithm; k-NN classifier; noise filtering; vision-based Infant Pain monitoring system; Educational institutions; Face detection; Image color analysis; Monitoring; Pain; Pediatrics; Skin; Detection of facial changes; NICU patient; knn classifier;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on

Conference_Location

Sanya

Print_ISBN

978-1-4673-2465-6

Type

conf

DOI

10.1109/MSNA.2012.6324597

Filename

6324597