DocumentCode :
495536
Title :
Validity Analysis of an Automatic Dynamic Electrocardiogram Waveform Selection Strategy
Author :
Gang, Zheng ; Tian, Yu ; Shanling, Mou ; Shiliu, Lian
Author_Institution :
Sch. of Comput. Sci. & Technol., Tianjin Univ. of Technol., Tianjin, China
Volume :
4
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
504
Lastpage :
507
Abstract :
The paper gives a validity analysis on an automatic dynamic electrocardiogram (Holter) waveform selection strategy. The strategy was based on machine learning techniques. And the data used in analysis are from clinic. The analysis showed that 93% can be reached in clustering phase, and 92% in classification phase. Although the result was not very satisfied, it was a good trying in this study area. In the future, along with improving of the validity, the strategy can take more effect on heart disease diagnosing.
Keywords :
diseases; electrocardiography; learning (artificial intelligence); medical diagnostic computing; medical signal processing; pattern clustering; signal classification; waveform analysis; Holter monitor; automatic dynamic electrocardiogram waveform selection strategy; classification phase; clustering phase; heart disease diagnosis; machine learning technique; validity analysis; Cardiac disease; Cities and towns; Computer science; Electrocardiography; Filters; Information analysis; Kernel; Laboratories; Machine learning; Paper technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.530
Filename :
5171047
Link To Document :
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