BAND-LIMITED MORPHOMETRIC ANALYSIS OF THE INTRACARDIAC SIGNAL - IMPLICATIONS FOR ANTITACHYCARDIA DEVICES

Inappropriate electrical therapy and power efficiency play a major rol e in algorithm implementation for antitachycardia devices (ATD) that c apture, store, and analyze the patient electrogram as an adjunct to ra te determination. Morphologically based algorithms have been demonstra ted to improve specificity thereby decreasing occurrences of inappropr iate electrical therapy. However, morphologically based algorithms are power demanding. Optimization of power efficiency can be achieved by eliminating unnecessary algorithmic computation, but must not compromi se the effectiveness of algorithms, which perform direct analysis on r aw signals. Significant reductions can be achieved by reduced sampling rates, which allow for increased overall ATD efficiency via concomita nt decreases in computation and data storage. This investigation deter mined the upper and lower bounds for filter cut-off frequency beyond w hich detection precision by an established morphometric method for arr hythmia classification, correlation waveform analysis (CWA), was unfav orable. Four measurement statistics were used. In ten patients with in ducible VT and VF, all bipolar intraventricular electrograms were clas sified correctly with a minimum passband of 10-50 Hz using any of the four measurement statistics. There was greater than or equal to 80% co rrect classification using all four measurement statistics with passba nds having low frequency cutoffs less than or equal to 15 Hz and high frequency cutoffs greater than or equal to 50 Hz. Correct classificati on of greater than or equal to 90% of unipolar electrograms during NSR , VT, and VF occurred using all four measurement statistics with a pas sband of 1-50 Hz. There was greater than or equal to 80% correct class ification with passbands 1, 10, 25, or 20-500 Hz and 10-50 Hz. The cla ssification of NSR, VT, and VF was most accurate on an intrapatient ba sis. Accuracy decreased using an interpatient rhythm classification. O ptimum filter settings of 1-50 Hz and 10-50 Hz were determined for uni polar and bipolar electrograms, respectively. Sampling data at 120 Hz was found to be sufficient. Bipolar electrode configuration statistica lly outperformed unipolar data. In conclusion, morphometric analysis o f bipolar and unipolar intraventricular electrograms appears to be ach ievable using band limited data and reduced sampling rates.