Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin

Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin

This thesis presents a research work on a diagnosis system for heart sound based on nonlinear ARX (NARX) model. The system uses neural network for model estimation and classification of several heart diseases. Six NARX models which represent Normal and other five categories of heart diseases such as...

Full description

Bibliographic Details
Main Author: Shamsuddin, Noraishah
Format: Book Section
Language:English
Published: Institute of Graduate Studies, UiTM 2012
Subjects:
Malaysia
R Medicine (General)
Online Access:http://ir.uitm.edu.my/id/eprint/19108/
http://ir.uitm.edu.my/id/eprint/19108/1/ABS_NORAISHAH%20SHAMSUDDIN%20TDRA%20VOL%201%20IGS%2012.pdf
id uitm-19108
recordtype eprints
spelling uitm-191082018-06-11T01:02:33Z http://ir.uitm.edu.my/id/eprint/19108/ Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin Shamsuddin, Noraishah Malaysia R Medicine (General) This thesis presents a research work on a diagnosis system for heart sound based on nonlinear ARX (NARX) model. The system uses neural network for model estimation and classification of several heart diseases. Six NARX models which represent Normal and other five categories of heart diseases such as Atrial Septal Defect (ASD), Pulmonary Stenosis (PS), Patent Ductus Arteriosus (PDA), Ventricular Septal Defect (VSD) and Mitral Regurgitation (MR) are estimated. A Lipschitz method and Levenberg Marquardt algorithm is used to determine the model order number and train the network respectively. The R-square value of the OSA prediction of the signal is above 99% for all heart sound signals. Institute of Graduate Studies, UiTM 2012 Book Section PeerReviewed text en http://ir.uitm.edu.my/id/eprint/19108/1/ABS_NORAISHAH%20SHAMSUDDIN%20TDRA%20VOL%201%20IGS%2012.pdf Shamsuddin, Noraishah (2012) Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin. In: The Doctoral Research Abstracts. IPSis Biannual Publication, 1 (1). Institute of Graduate Studies, UiTM.
repository_type Digital Repository
institution_category Local University
institution Universiti Teknologi MARA
building UiTM Institutional Repository
collection Online Access
language English
topic Malaysia
R Medicine (General)
spellingShingle Malaysia
R Medicine (General)
Shamsuddin, Noraishah
Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin
description This thesis presents a research work on a diagnosis system for heart sound based on nonlinear ARX (NARX) model. The system uses neural network for model estimation and classification of several heart diseases. Six NARX models which represent Normal and other five categories of heart diseases such as Atrial Septal Defect (ASD), Pulmonary Stenosis (PS), Patent Ductus Arteriosus (PDA), Ventricular Septal Defect (VSD) and Mitral Regurgitation (MR) are estimated. A Lipschitz method and Levenberg Marquardt algorithm is used to determine the model order number and train the network respectively. The R-square value of the OSA prediction of the signal is above 99% for all heart sound signals.
format Book Section
author Shamsuddin, Noraishah
author_facet Shamsuddin, Noraishah
author_sort Shamsuddin, Noraishah
title Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin
title_short Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin
title_full Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin
title_fullStr Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin
title_full_unstemmed Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin
title_sort heart sound diagnosis using nonlinear arx model / noraishah shamsuddin
publisher Institute of Graduate Studies, UiTM
publishDate 2012
url http://ir.uitm.edu.my/id/eprint/19108/
http://ir.uitm.edu.my/id/eprint/19108/1/ABS_NORAISHAH%20SHAMSUDDIN%20TDRA%20VOL%201%20IGS%2012.pdf
first_indexed 2023-09-18T23:01:52Z
last_indexed 2023-09-18T23:01:52Z
_version_ 1777418226804719616

Similar Items