Open AccessComparison of Normal and Abnormal Conditions in ECG Using RR Variablity and Spectral Density
Author(s) -
T. R. Thamizhvani,
Josline Elsa Joseph,
Bincy Babu,
U Rithikka,
Dakshayani.K K.R.Rohini,
A Josephin Arockia Dhivya
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.25.12362
Subject(s) - qrs complex , spectral density , cardiology , abnormality , waveform , electrocardiography , medicine , signal (programming language) , atrial fibrillation , pattern recognition (psychology) , mathematics , artificial intelligence , computer science , statistics , telecommunications , radar , psychiatry , programming language
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.