Heart diseases require early detection and long term monitoring to save life’s of Cardiac patients. Measurement of abnormalities found in heart rate due to disturbances in electrical activity of heart ,  is the easiest way to detect cardiac diseases. The best electronic machine for this purpose is ECG, which plays a vital role in the discrimination of normal heart beat from abnormal one, it is called ECG arrhythmia. This paper is based on automatic detection and classification ofvarious cardiac arrhythmiawhich is illustrated in dynamic features and morphological patterns of ECG signals. MIT BIH arrhythmia database is used for ECG input from literature.