Filtering of the Intraventricular Electrogram and Its Effect on Signal Detection

Morphological waveform identification methods have been demonstrated to be effective for distinction of normal and abnormal conduction in intraventricular electrograms in small pilot tests. Yet these methods will find acceptance in future implantable devices only when computational demands and memory requirements are further reduced. A restricted passband allows reduced sampling rate and diminished storage for microprocessor based devices. In this study, we wished to determine the narrowest bandwidth that could be tolerated by a signal analy'sis morphometric (CWA) in order to distinguish ventricular tachycardia ( V T ) from sinus rhythm (SR). Twenty-five paired sets of bipolar intracardiac S R and monomorphic VT passages were analyzed. These signals were subjected to thirty-two different combinations of filter settings. Correlation coeficients were computed on a cycle-bycycle basis for each signal passage to separate SR and VT. An absolute separation of ranges of CWA values was used as a discriminant function. Our results showed that a high frequency cutoff of 80 Hz yielded adquate performance of morphological separation of normal and abnormal rhythm, given that low frequency cutoff was no higher than 10 Hz. Low pass filtering has minor impact on the performance of CWA compared to high pass filtering.