Comparison of Normal and Abnormal Conditions in ECG Using RR Variablity and Spectral Density

Abstract

Abnormality of the heart is monitored by Electrocardiograph (ECG). The ECG waveform is formed of PQRS pattern. Differentiation of the abnormalities based on the ECG signal is simple algorithm for diagnosis. ECG data of normal, atrial fibrillation and congestive heart failure is obtained from a authorized database. R peak from the QRS complex is detected using Pan-Tompkins algorithm for analysis. Mean RR and heart rate variability parameters are extracted from the QRS complex detected. With these results, the difference in the three ECG signals can be determined. For further detailed comparison, frequency component variation is analysed using power spectral density. Based on density spectrum, the differentiation of normal and abnormal ECG signals can be determined.

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“…They also investigated the effect of slow ventricular activation on the QRS complex and showed how alteration of electrical properties might mimic ECG morphologies associated with anatomical abnormal-ities. Thamizhvani et al (2018) monitors the abnormality of the heart by Electrocardiograph (ECG) waveform, which is formed of the PQRS pattern. Differentiation of the abnormalities based on the ECG signal can be applied for diagnosis in a clinical setting.…”