Analysis of ST Segment Variability in ECG Using Discrete Wavelet Transform

In recent years the cardiac arrest has become most frequent cause of death. The cardiac arrest normally occurs when the electrical impulses, which excite ventricles, turn into irregular. This state is known as ischemia and leading to Arrhythmias and Acute Myocardial Infarction (AMI). This paper gives a novel method to analyze ST-Segment Variability (STV) and to detect ischemia using the Discrete Wavelet Transform (DWT). DWT is an effective tool for analyzing ECG signals. The proposed method involves first processing ECG with digital filters to remove powerline interference, motion artifacts and baseline wander. Later, the ECG is processed with Wavelet Transform to enhance the QRS complex. Next simple algorithms are used to detect fiducial points, QRS complex and J point of each detected QRS complex. Finally ST-segment is extracted for every detected J point and ischemic ST beats are identified. The ischemia is estimated by performing statistical analysis such as finding variance of ischemic ST-Segments and all ST- Segments. The proposed method was tested on MIT-BIH database.