DocumentCode :
3117043
Title :
Discrimination of Myocardial Infraction Using Orthogonal ECG and Fuzzy Weighted Method
Author :
Ge Dingfei ; Sun Lihui ; Wen Xiaojun
Author_Institution :
Sch. of Inf. & Electron. Eng., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
fYear :
2010
fDate :
18-20 June 2010
Firstpage :
1
Lastpage :
4
Abstract :
The abnormal changes of different myocardial infarction(MI) evolution stages appeared in Electrocardiogram(ECG) are low-level signals even under the high resolution condition. A method for enhancement of the low-level ECG signals in the signal averaged ECG was introduced in order to discriminate MI stages. High Resolution orthogonal Frank leads (orthogonal ECG,OECG) were analysed aiming to provide adequate information about MI stages in the study. The method includes the derivation of weighting value and computation of weighted OECG waveforms. Three OECG leads were transformed from 12-standard ECG leads by existing approach. The experimental results show the better features can be obtained from weighted OECG waveforms based on the proposed method compared with conventional signal averaging method. It is possible to classify MI stages for practical clinical diagnosis purpose.
Keywords :
diseases; electrocardiography; fuzzy logic; medical signal processing; electrocardiogram; fuzzy weighted method; high resolution orthogonal Frank leads; low level signal enhancement; myocardial infarction evolution stages; myocardial infraction discrimination; orthogonal ECG; signal averaged ECG; weighted OECG waveforms; Biomedical engineering; Data mining; Electrocardiography; Heart; Information analysis; Medical diagnostic imaging; Myocardium; Signal resolution; Signal to noise ratio; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
Conference_Location :
Chengdu
ISSN :
2151-7614
Print_ISBN :
978-1-4244-4712-1
Electronic_ISBN :
2151-7614
Type :
conf
DOI :
10.1109/ICBBE.2010.5516250
Filename :
5516250
Link To Document :
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