Automatic detection of ventricular tachycardia and fibrillation using ECG processing and intramyocardial pressure...

Ventricular electrograms and intramyocardial pressure signals were recorded in 11 dogs during sinus rhythm, during paced ventricular tachycardia, and at the onset of and during ventricular fibrillation. The autocorrelation function and the probability density function of short episodes of the electrograms were analyzed off-line on a digital computer. Peak-to-peak values of the intramyocardial pressure were calculated during sinus rhythm and during ventricular tachycardia and fibrillation. An algorithm was developed to recognize tachycardia and fibrillation using the autocorrelation function, the probability density function, and the intramyocardial pressure as input signals. Results show that in case of sinus rhythm all detection methods are reliable (recognition rate of 100%). In case of ventricular tachycardia with hemodynamic impairment the autocorrelation function is slightly better (66.6%) than the probability density function (44.4%). The onset of ventricular fibrillation is sensed in 81.8% of all episodes with the autocorrelation function and in 63.6% with the probability density function. During ventricular fibrillation this improves, respectively, to 92.3 and 69.2%. In all previous cases the intramyocardial pressure signal was 100% reliable. It is concluded that in this arrhythmia model, the sensitivity of an automatic ventricular tachycardia/fibrillation detection system was increased by combining ECG processing with analysis of an hemodynamic parameter.