Improved Spectrogram Analysis for ECG Signal in Emergency Medical Applications

Abstract

This paper presents the spectrogram effect of biomedical signal, especially for ECG. Simulation module developed for the spectrogram implementation. Spectrogram based on ECG signal and power spectral density together with off-line evaluation has been observed. ECG contains very important clinical information about the cardiac activities of heart. The features of small variations in ECG signal with time-varying morphological characteristics needs to be extracted by signal processing method because there are not visible of graphical ECG signal. Small variations of simulated normal and noise corrupted ECG signal have been extracted using spectrogram. The spectrogram found to be more precise over conventional FFT in finding the small abnormalities in ECG signal. These form time-frequency representations for processing time-varying signals. By using the presented method, it is ensure that high resolution time-varying spectrum estimation with no lag error can be produced. Other benefits of the method are the straightforward procedure for evaluating the statistics of the spectrum estimation.