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Identification of normal and pain infants based on individual crying pattern

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Bibliographic Details
Main Author: Ezzatul Deanna Erni, Mohamad Azmi
Other Authors: Dr. Puteh Saad
Format: Learning Object
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2016
Subjects:
Infant
Crying pattern
Crying pattern signal
Radial Basis Function Neural Network (RBF)
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41733
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spelling my.unimap-417332016-05-29T07:49:21Z Identification of normal and pain infants based on individual crying pattern Ezzatul Deanna Erni, Mohamad Azmi Dr. Puteh Saad Infant Crying pattern Crying pattern signal Radial Basis Function Neural Network (RBF) Access is limited to UniMAP community. An Infant informs his or her needs to those around them by crying. It is difficult for us adults to exactly know the message associated with each crying pattern. In this endeavour, a normal cry and a cry associated with pain will be identified using a signal processing approach. There are four processes involved; first stage is to filter the signal using pre-emphasis filter, then to perform feature extraction using Melfrequency cepstral coefficient (MFCC) and finally to classify the features into normal cry pattern and pain cry pattern using Radial Basis Function Neural Network (RBF). The accuracy achieved is 92.3%. Thus, the RBF has the potential to be utilized as a classifier for crying pattern signals. 2016-05-29T07:49:21Z 2016-05-29T07:49:21Z 2015-06 Learning Object http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41733 en Universiti Malaysia Perlis (UniMAP) School of Computer and Communication Engineering
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 Infant
Crying pattern
Crying pattern signal
Radial Basis Function Neural Network (RBF)
spellingShingle Infant
Crying pattern
Crying pattern signal
Radial Basis Function Neural Network (RBF)
Ezzatul Deanna Erni, Mohamad Azmi
Identification of normal and pain infants based on individual crying pattern
description Access is limited to UniMAP community.
author2 Dr. Puteh Saad
author_facet Dr. Puteh Saad
Ezzatul Deanna Erni, Mohamad Azmi
format Learning Object
author Ezzatul Deanna Erni, Mohamad Azmi
author_sort Ezzatul Deanna Erni, Mohamad Azmi
title Identification of normal and pain infants based on individual crying pattern
title_short Identification of normal and pain infants based on individual crying pattern
title_full Identification of normal and pain infants based on individual crying pattern
title_fullStr Identification of normal and pain infants based on individual crying pattern
title_full_unstemmed Identification of normal and pain infants based on individual crying pattern
title_sort identification of normal and pain infants based on individual crying pattern
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2016
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41733
_version_ 1643799767617110016
score 13.214268

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