EXPLORING CWT BASED ALGORITHM AS ADDITIONAL AND ACCURATE TOOL FOR DETECTING ECG ABNORMALITIES

• Published in: Acta Technica Corvininesis Vol. 13; no. 4; pp. 35 - 40
• Main Author: Stănescu, Mariana Mirela
• Format: Journal Article
• Language: English
• Published: Hunedoara Faculty of Engineering Hunedoara 01-10-2020
• Subjects: Abnormalities; Algorithms; Atria; Bradycardia; Cardiac arrhythmia; Cardiovascular disease; Classification; Depolarization; Electrocardiography; Fourier transforms; Heart; Heart rate; Ischemia; Noise; P waves; Tachycardia; Wavelet transforms
• ISSN: 2067-3809

Keywords: ECG features, coronary disease, ischemia, Db wavelet, MATLAB References: INTRODUCTION The electrocardiogram (ECG) is a graphical recording of the direction and magnitude of heart electrical activity, which is generated by depolarization and repolarization of atria and ventricles. The development of the methods of automatic extraction of accurate and rapid information characteristic of ECG is of major importance for the long term analysis of ECG signals [7]. Another ECG-shape suitable wavelet is Db5 (Figure 5). (a) Wavelet function ф DB5, (b) Scaling function ф The detection of P wave, QRS complex and T wave in an ECG signal is a difficult problem due to the variation in time of signal, physiological conditions and the presence of noise. Like all signals from the Physionet database, these sample recordings are noted for normal heart rate, RR intervals, presence of premature atrial (APC) and ventricular (PVC) contractions), tachycardia and bradycardia episodes, branch blockages (BBB; RBBB; LBBB), etc.