Using wavelet transform in biomedical engineering – heart signal analysis
In previous post, we cleared out that wavelet transform is used to analyze short-time and non-stationary signals. Since base wavelet function has to parameters – translation and scaling, it is possible to achieve good time and frequency localization. In other words, we can equally analyze the slow signal and fast signal structures without losing resolution and so evaluate signal frequency characteristics and time dynamics. Heart signal analysis is one of the most common problems in biomedical engineering. Practically every part of ECG signal carries some sort of information about heart conditions, possible pathologies, and diseases. So equally, frequency and timing characteristics of ECG signal is essential. As you know standard ECG signal consists of several typical waveforms like P-QRS-T, where in P and T waves low frequency component dominates, and in QRS, mid and high. The common condition of hear is myocardial ischemia when blood flow through coronary arteries to the heart is reduced, what prevents receiving enough oxygen. This can damage the heart muscle and lead to a heart attack. In order to notice this pathology it is we need to analyze S-T segment of ECG waveform. Insignificant changes in the signal can indicate ischemia. In order to find…
