ECG signal analysis for detection of cardiovascular abnormalities and ischemic episodes

摘要

Electrocardiogram (ECG) is generally used for diagnosis of cardiovascular abnormalities and heart disorders. An efficient method for analyzing the ECG signal towards the detection of cardiovascular abnormalities and ischemic episodes follows mainly five stages: pre-processing, feature extraction, cardiac abnormality detection, beat classification and ischemic episode recognition. The detection of cardiovascular abnormalities like bradycardia and tachycardia is based on the calculation of heart rate(HR) from the extracted ECG features. The extracted ST-segment and T-wave features are used for detection of ischemic episodes. The ability of the method was tested on European ST-T database. The performance of ischemic episode detection shows 88.08% sensitivity (Se) and 92.42% positive predictive accuracy (PPA).