alexa Analysis of Capnogram Using Linear Predictive Coding (L
ISSN: 2157-7552

Journal of Tissue Science & Engineering
Open Access

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Research Article

Analysis of Capnogram Using Linear Predictive Coding (LPC) to Differentiate Asthmatic Conditions

M Kazemi* and MB Malarvili

Faculty of Biomedical Engineering and Health Science, Universiti Teknologi Malaysia, Malaysia

Corresponding Author:
Dr. M. Kazemi
Faculty of Biomedical Engineering and Health Science
University Technology Malaysia, Malaysia
E-mail: [email protected]

Received date: November 21, 2011; Accepted date: November 30, 2011; Published date: December 02, 2011

Citation: Kazemi M, Malarvili MB (2011) Analysis of Capnogram Using Linear Predictive Coding (LPC) to Differentiate Asthmatic Conditions. J Tissue Sci Eng 2:111. doi:10.4172/2157-7552.1000111

Copyright: © 2011 Yamano S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

In this paper, an analysis of capnogram to differentiate asthmatic and non-asthmatic patients is presented by using linear predictive coding (LPC) technique. In the previous studies, manual study on capnogram signal has been conducted by several researchers. All previous researches show significant correlation between the capnogram and asthmatic patient. However all of them are just manual study conducted through the conventional time domain method. In this preliminary, a number of 8 LPC coefficients (α1- α8) for both asthmatic (CAP) and non-asthmatic patients’ capnogram (CNP) are extracted. Usefulness and performance of these coefficients to differentiate the asthmatic conditions by means of receiver operating characteristic (ROC) curve analysis are shown. Our preliminary results show that α3, α4, α5, and α6 can be used to distinguish the asthmatic conditions.

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