Time-Frequency Analysis for Arrhythmia Discrimination Using Human Atrium Electrogram

Detection methods for atrial tachycardia and fibrillation on the time axis have the advantages of light operational load and are easy to apply to various applications. Despite these advantages, arrhythmia detection algorithm on the time axis cannot stand much noise such as motion artifacts, moreover the peak detection algorithm has high complexity. In this paper, we use a spectrum analysis method for the detection of atrial tachycardia and fibrillation. By applying spectrum analysis and digital filtering on obtained electrogram signals, we can diagnose cardiac arrhythmia without using peak detection algorithm

[1]  J.L. Rojo-Alvarez,et al.  Discriminating between supraventricular and ventricular tachycardias from EGM onset analysis , 2002, IEEE Engineering in Medicine and Biology Magazine.

[2]  J. M. Jenkins,et al.  Detection algorithms in implantable cardioverter defibrillators , 1996, Proc. IEEE.

[3]  Andrea Baschirotto,et al.  A 1 V 1.2 /spl mu/W 4th order bandpass switched-opamp SC filter for a cardiac pacer sensing stage , 2000, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).