Journal Homepage: www.ijcst.org

Abstract – Chest pain is an early sign of a person experiencing cardiac function abnormalities. Characteristic changes in ST segment elevation of ST segments which can be followed by T wave inversion is an early sign of heart dysfunction. In this paper, the ST segment of the electrocardiogram signal will be identified using new wavelet methods. Specific form of the electrocardiogram signal which gives angle, amplitude, phase and certain frequency is used as the basis of new wavelet DeGeSTSeg formation. The first thing to do is to detect the R peak of the electrocardiogram signal. Furthermore, the Q signal and the S signal is detected after the R signal is determined. ST segment was detected after all components of the signal are identified. The Basis of DeGeSTSeg is a new wavelet to detect the ST segment of the electrocardiogram signal. The originality of this study is applied to the electrocardiogram signal ST segment, with varying leads and was analyzed for each component Q, R, S and ST segment of the electrocardiogram signal. The results show the effectiveness of the utility DeGeSTSeg wavelet algorithm to detect the wave of the electrocardiogram STSegmen 6-lead electrocardiogram. With the sensitivity = 93 % by using Receiver Operating characteristics of the community (ROC) curve