Title :
New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data
Author :
Safdarian, N. ; Dabanloo, N.J. ; Attarodi, G.
Author_Institution :
Biomed. Eng., Islamic Azad Univ., Tehran, Iran
Abstract :
In this study, a method for determining the location and extent of myocardial infarction using BSPM data that was obtained from PhysioNet challenge 2007 database has been suggested. This data is related to the four patients with MI that we used from two patients as training set to determine rules, and from two other patients for testing set and the conclusion of the proposed model. At first, T-wave amplitude, R-wave amplitude and integration of T-wave as three features of ECG signals were extracted. Then with definition and applying several rules and threshold levels for those features, areas that are with MI and these extents were diagnosed. In this study to determine the precise location of MI, 17-segments standard model of left ventricle (LV) was used. Finally, overall accuracy of this method that expressed with SO parameter and EPD parameter for two patients in test set was obtained to 0.94 and 5.37, respectively. The main advantages of this method were its simplicity and high accuracy.
Keywords :
diseases; electrocardiography; feature extraction; medical signal detection; medical signal processing; surface potential; BSPM data; ECG signal feature extraction; EPD parameter; PhysioNet challenge 2007 database; R-wave amplitude; SO parameter; T-wave amplitude; T-wave integration; body surface potential map data; detection method; left ventricle; myocardial infarction; standard model; testing set; threshold levels; training set; Databases; Electrocardiography; Feature extraction; Mathematical model; Myocardium; Torso; Training;
Conference_Titel :
Computing in Cardiology (CinC), 2012
Conference_Location :
Krakow
Print_ISBN :
978-1-4673-2076-4