Digital signal processing chip implementation for detection and analysis of intracardiac electrograms.

Abstract

The adoption of digital signal processing (DSP) microchips for detection and analysis of electrocardiographic signals offers a means for increased computational speed and the opportunity for design of customized architecture to address real-time requirements. A system using the Motorola 56001 DSP chip has been designed to realize cycle-by-cycle detection (triggering) and waveform analysis using a time-domain template matching technique, correlation waveform analysis (CWA). The system digitally samples an electrocardiographic signal at 1000 Hz, incorporates an adaptive trigger for detection of cardiac events, and classifies each waveform as normal or abnormal. Ten paired sets of single-chamber bipolar intracardiac electrograms (1-500 Hz) were processed with each pair containing a sinus rhythm (SR) passage and a corresponding arrhythmia segment from the same patient. Four of ten paired sets contained intraatrial electrograms that exhibited retrograde atrial conduction during ventricular pacing; the remaining six paired sets of intraventricular electrograms consisted of either ventricular tachycardia (4) or paced ventricular rhythm (2). Of 2,978 depolarizations in the test set, the adaptive trigger failed to detect 6 (99.8% detection sensitivity) and had 11 false triggers (99.6% specificity). Using patient dependent thresholds for CWA to classify waveforms, the program correctly identified 1,175 of 1,197 (98.2% specificity) sinus rhythm depolarizations and 1,771 of 1,781 (99.4% sensitivity) abnormal depolarizations. From the results, the algorithm appears to hold potential for applications such as real-time monitoring of electrophysiology studies or detection and classification of tachycardias in implantable antitachycardia devices.