Application of Wavelet Based Denoising for T-Wave Alternans Analysis in High Resolution ECG Maps
T-wave alternans (TWA) allows for identification of patients at an increased risk of ventricular arrhythmia. Stress test, which increases heart rate in controlled manner, is used for TWA measurement. However, the TWA detection and analysis are often disturbed by muscular interference. The evaluation of wavelet based denoising methods was performed to find optimal algorithm for TWA analysis. ECG signals recorded in twelve patients with cardiac disease were analyzed. In seven of them significant T-wave alternans magnitude was detected. The application of wavelet based denoising method in the pre-processing stage increases the T-wave alternans magnitude as well as the number of BSPM signals where TWA was detected.
Identification of Ischemic Lesions Based on Difference Integral Maps, Comparison of Several ECG Intervals
Ischemic changes in small areas of myocardium can be detected from difference integral maps computed from body surface potentials measured on the same subject in situations with and without manifestation of ischemia. The proposed method for their detection is the inverse solution with 2 dipoles. Surface potentials were recorded at rest and during stress on 10 patients and 3 healthy subjects. Difference integral maps were computed for 4 intervals of integration of electrocardiographic signal (QRST, QRSU, STT and STU) and their properties and applicability as input data for inverse identification of ischemic lesions were compared. The results showed that better (more reliable) inverse solutions can be obtained from difference integral maps computed either from QRST or from STT interval of integration. The average correlation between these maps was 97%. The use of the end of U wave instead of the end of T wave for interval of integration did not improve the results.