Spectrogram as an Emerging Tool in ECG Signal Processing

Abstract

These days signal processing has the great importance in extracting important pathological attributes of the subject (patient). This paper covers important aspects of Electrocardiogram (ECG) signal analysis by proposing emerging tool. The degree of morphological beat-to-beat variability has been examined using a spectrogram technique on real-time ECG datasets. It provides time varying spectral density description of the ECG signal. Out of 49,181 total beats, the proposed technique presents duplicity (D) of 0.4% and detection rate (DR) of 99.48%. Some of the possible future directions, that the research work carried out in this paper can take, are also outlined in conclusion section.