AUTOMATIC DETECTION OF VENTRICULAR-TACHYCARDIA AND FIBRILLATION USINGECG PROCESSING AND INTRAMYOCARDIAL PRESSURE MEASUREMENT

Ventricular electrograms and intramyocardial pressure signals were rec orded in 11 dogs during sinus rhythm, during paced ventricular tachyca rdia, and at the onset of and during ventricular fibrillation. The aut ocorrelation function and the probability density function of short ep isodes of the electrograms were analyzed off-line on a digital compute r. Peak-to-peak values of the intramyocardial pressure were calculated during sinus rhythm and during ventricular tachycardia and fibrillati on. An algorithm was developed to recognize tachycardia and fibrillati on using the autocorrelation function, the probability density functio n, and the intramyocardial pressure as input signals. Results show tha t in case of sinus rhythm all detection methods are reliable (recognit ion rate of 100%). In case of ventricular tachycardia with hemodynamic impairment the autocorrelation function is slightly better (66.6%) th an the probability density function (44.4%). The onset of ventricular fibrillation is sensed in 81.8% of all episodes with the autocorrelati on 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 sensitiv ity of an automatic ventricular tachycardia/fibrillation detection sys tem was increased by combining ECG processing with analysis of an hemo dynamic parameter. (C) 1994 Academic Press, Inc.