Title :
Early diagnosis of acute coronary syndromes with automatic ST/T classifier
Author :
Terzi, Merve Begum ; Arikan, Orhan ; Abaci, Adnan ; Candemir, Mustafa ; Dedoglu, Mehmet
Author_Institution :
Elektrik ve Elektron. Muhendisligi Bolumu, Bilkent Univ., Ankara, Turkey
Abstract :
In patients with acute coronary syndrome, temporary chest pains together with changes in ECG ST segment and T wave occur shortly before the start of myocardial infarction. In order to diagnose acute coronary syndromes early, a new technique which detects changes in ECG ST/T sections is developed. As a result of implementing the developed technique to real ECG recordings, it is shown that the proposed technique provides reliable detections. Therefore, the developed technique is expected to provide early diagnosis of acute coronary syndromes which will lead to a significant decrease in heart failure and mortality rates.
Keywords :
biomedical engineering; diseases; electrocardiography; patient diagnosis; ECG ST segment; ECG ST-T section; ECG T wave; ECG recording; acute coronary syndrome diagnosis; automatic ST-T classifier; chest pain; heart failure; mortality rate; myocardial infarction; Diseases; Electrocardiography; Heart; Kernel; Myocardium; Neural networks; Support vector machines; Electrocardiogram (ECG) signal classification; acute coronary syndrome; acute myocardial infarction; feature detection; kernel method; support vector machine (SVM);
Conference_Titel :
Biomedical Engineering Meeting (BIYOMUT), 2014 18th National
Conference_Location :
Istanbul
DOI :
10.1109/BIYOMUT.2014.7026388