Automatic Detection of ECG R-R Interval using Discrete Wavelet Transformation

TLDR: An algorithm has been developed to preprocess and to automatically determine the R-R interval of ECG signal based on Discrete Wavelet Transformation (DWT) and the accuracy of the analysis can be increased and the analysis time can be reduced.

Abstract: Detection of QRS-complexes takes an important role in the analysis of ECG signal, based on which the number of heart beats and an irregularity of a heart beat through R-R interval can be determined. Since an ECG may be of different lengths and as being a non-stationary signal, the irregularity may not be periodic instead it can be shown up at any interval of the signal, it is difficult for physician to analyze ECG manually. In the present study an algorithm has been developed to preprocess and to automatically determine the R-R interval of ECG signal based on Discrete Wavelet Transformation (DWT). The developed algorithm initially performs preprocessing of a signal in order to remove Baseline Drift (De-trending) and noise (De-noising) from the signal and then it uses the preprocessed signal for finding R-R interval of the ECG signal automatically. By using developed algorithm, the accuracy of the analysis can be increased and the analysis time can be reduced. Keywords-ECG, QRS-complex, R-R interval, DWT, Baseline Drift, De-noising. I. INTRODUCTION The Electrocardiogram (ECG or EKG) is a graphic record of the direction and magnitude of electrical activity of the heart that is generated by depolarization and repolarization of the atria and ventricles (1). Depolarization occurs when the cardiac cell, which are electrically polarized, lose their internal negativity. The spread of depolarization travels from cell to cell, producing a wave of depolarization across the entire heart. This wave represents a flow of electricity that can be detected by electrodes placed on the surface of the body. Once depolarization is completed the cardiac cells are restored to their resting potential, a process called repolarization. This flow of energy takes in the form of ECG wave and is composed of P wave followed by QRS complex followed by T wave followed by U wave per cardiac cycle which is shown in Fig. 1. The P wave is a small low-voltage deflection away from the baseline caused by the depolarization of the atria prior to atria contraction. QRS-complex is the largest-amplitude portion of the ECG, caused by currents generated when the ventricles depolarize prior to their contraction. The T-wave is the result of ventricular repolarization and finally the small U wave although not always visible, is considered to be a representation of the Papillary Muscle or Purkinje Fibers. Generally, the condition of a heart can be determined by extracting features (2) from the ECG signal. These features include the amplitudes of the waves and the intervals between them. A normal ECG signal has the following amplitudes values: P-wave 0.25 mV, R-wave 1.6mV, Q-wave 25% of the R-wave, T-wave 0.1 to 0.5 mV; the time interval values: PR-interval 0.12-0.2s, QRS complex 0.04 to 0.12s, QT interval <0.42s and the heart rate of 60-100 beats/min (3). Any change in the above said values indicates the abnormality of the heart. Vanisree K et al. / International Journal on Computer Science and Engineering (IJCSE)