Comparison of characterizing and data analysis methods for detecting abnormalities in ECG

The electrocardiogram (ECG) is an important bioelectrical signal which gives valuable information about the functional aspects of the heart both in normal and abnormal conditions. For several decades a considerable amount of research activity has been directed towards advancement in the clinical diagnosing of this disease using surface ECG and symptoms. This paper compares different methods that have evolved over the years for elimination of different types of noise present in ECG and for characterizing ECG for the detection of myocardial ischemia and infarction which is a life threatening heart disease. The first part of the review gives broad overview of the research undergone in the area of denoising methods deployed and second part describes different types of ischemia and methods to detect the disease using ECG.