An algorithm of ST segment classification and detection

Author

Shen, Zhao ; Hu, Chao ; Liao, Jingsheng ; Meng, Max Q H

Author_Institution

Inst. of Autom., Northwestern Polytech. Univ., Xi´´an, China

fYear

2010

fDate

16-20 Aug. 2010

Firstpage

559

Lastpage

564

Abstract

In electrocardiogram real-time monitoring, the ST segment detection is important, it has close relationship with myocardial ischemia and myocardial infarction. In this paper, ST detection is divided into two parts, firstly using wavelet and morphology method to calculate the offset direction, waveform and summarizing features of ST, eventually divide the ST in 15 types; next analyzing the ST waveform change tendency in about 30 minutes and discovering the rhythm of ischemia or infarction to help doctor. At last, the first part has been confirmed by MIT-BIH Arrhythmia database and European ST-T database and the second is proved by two experts´ conclusion.

Keywords

diseases; electrocardiography; mathematical morphology; medical signal detection; medical signal processing; patient monitoring; signal classification; wavelet transforms; European ST-T database; MIT-BIH arrhythmia database; ST segment classification; ST segment detection; electrocardiogram real-time monitoring; morphology method; myocardial infarction; myocardial ischemia; offset direction; wavelet transform; Diseases; Electrocardiography; Heart; ISO; Myocardium; Noise; Wavelet analysis; R wave; ST segment; T wave; wavelet;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics (ICAL), 2010 IEEE International Conference on

Conference_Location

Hong Kong and Macau

Print_ISBN

978-1-4244-8375-4

Electronic_ISBN

978-1-4244-8374-7

Type

conf

DOI

10.1109/ICAL.2010.5585348

Filename

5585348