Ventricular tachyarrhythmias, in particular
ventricular fibrillation (VF), are the primary arrhythmic events in the majority of patients suffering from
sudden cardiac death. Attention has focused upon these articular rhythms as it is recognized that prompt
therapy can lead to a successful outcome. There has been considerable interest in analysis of the surface electrocardiogram (ECG) in VF centred on attempts to understand the pathophysiological processes occurring in
sudden cardiac death, predicting the efficacy of
therapy, and guiding the use of alternative or adjunct
therapies to improve
resuscitation success rates.
Atrial fibrillation (AF) and
ventricular tachycardia (VT) are other types of
tachyarrhythmias that constitute a medical challenge. In this paper, a high order spectral analysis technique is suggested for quantitative analysis and classification of
cardiac arrhythmias. The algorithm is based upon bispectral analysis techniques. The bispectrum is estimated using an AR model, and the frequency support of the bispectrum is extracted as a quantitative measure to classify atrial and
ventricular tachyarrhythmias. Results show a significant difference in the parameter values for different arrhythmias. Moreover, the bicoherency spectrum shows different bicoherency values for normal and
tachycardia patients. In particular, the bicoherency indicates that phase coupling decreases as
arrhythmia kicks in.