ST-T complex automatic analysis of the electrocardiogram signals based on wavelet transform

ST-T complex automatic analysis of the electrocardiogram (ECG) signals was investigated. First, a wavelet adaptive filter structure was used to remove the baseline wandering of the ECG signals, which was critically important for ST segment analysis. Then, taking advantages of the multiple resolution ability of the wavelet transform, an identification method was developed to identify the ST segment fiducial points of the ECG signals at different wavelet decomposition scales or frequency bands. The proposed methods were tested using the standard MIT/BIH ECG ST segment database. The fiducial points identification results were compared with those obtained manually by the experienced cardiologists. This comparison showed a good matching, which suggested the reliability of the proposed method.