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Rough set theory and automatic analysis of ECG
Author: ZhangYong
Tutor: ShuLan
School: University of Electronic Science and Technology
Course: Applied Mathematics
Keywords: Rough Set Decision Tables Simplify ECG Feature points QRS complex R wave
CLC: R311
Type: Master's thesis
Year: 2000
Downloads: 158
Quote: 6
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Abstract
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In this paper, based on rough set theory , rough set decision table simplified theory and rough set decision table simplified method for the identification of ECG feature points , a the ECG feature point identification simplify rules , the use of these simplified rules can effectively identify ECG feature points . This paper also proposed a method to determine the characteristic elements like - characteristic determination algorithm , and the method used for ECG characteristic points of identification , to improve the accuracy of ECG feature points identified . ECG feature points in this article will also simplify the decision-making table identification rules and characteristics determination algorithm combined validation and discussion of the results in the simplified decision table . The principle difference method , k -point difference in the method for determining the \ECG automatic analysis algorithms , such as the R-wave recognition , recognition of the QRS wave starting and ending points , the P wave , T wave recognition algorithms , data verification by the MIT-BIH 8 hours to get the R-wave detection rate of 95.65% on average . ECG feature points obtained by using decision tables to simplify identification rules on the recognition of the R-wave detection rate slightly higher than the conventional identification methods . This algorithm using MATLAB mathematical software to program implementation ; Meanwhile, in order to facilitate the research and development of automatic ECG analysis algorithm , also developed the set used for ECG automatic analysis algorithm MATLAB toolkit for ECG automatic diagnosis and laid the foundation .
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