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