Raghukumar B S

Dr. Naveen B

Abstract

Feature extraction from ECG graph play a major role in diagnosing the heart abnormality. As the huge growth of medical image processing many research scholars, scientists have worked effectively on feature extraction from the graphical images of ECG report. Heart assault examine by a specialist is old and required exceptionally prolonged stretch of time to recognize stroke. The important thing of this work is to offer very little time to study the graphical ECG reports and give the required information for the further treatment. Recognizing coronary failure from the ECG report is demanding because of confusion, carelessness, delay, distinctive among the individuals dependent on age, gender, etc. Several methods are incorporated to extract feature from ECG reports are morphological analysis, Independent Component analysis (ICA) leads to effective identification of several abnormality of a heart and will diminish the misguided judgment, misconception of graphical ECG reports. So the significant thing of the work is to outfit an examination on the exactness of generally utilized algorithms by researchers and scientists in separating features from the ECG reports. In this paper, the consequences of different strategies for separating feature from the ECG reports have been examined vivaciously and this correlation examination work causes the inquires about to back out the time multifaceted nature they find in looking for changed combinational work.

Keywords- ECG reports, ICA, morphological analysis