Automated electrocardiography and arrhythmia monitoring.

C OMPUTER PROCESSING of the electrocardiographic signal (ECG) began over two decades ago when Dr. Hubert V. Pipberger undertook a project for the Veterans Administration in which he employed a digital computer for the automated detection of ECG waveforms. The original attempt at automation merely delineated and measured the P, QRS, and T waves, detecting the onset and termination of each wave, and measured intervals between waves. Contour analysis of the waveforms followed and, as this technique became more highly developed, Pipberger and others began to apply decision tree logic to the results in order to arrive at a specific diagnostic interpretation. At a later stage, second generation programs were designed that employed statistical methods for diagnosis. Clinical implementation of computerized elcctrocardiography occurred in the early 1970s and has continued to develop at a rapid rate. Computerized electrocardiography falls into two broad categories: computer-assisted interpretation of the diagnostic ECG and computer monitoring of cardiac arrhythmias. In the first category, pattern recognition techniques are applied to an ECG signal that has been previously acquired and stored in a digital computer for examination at length. In arrhythmia monitoring the dynamic ECG signal is analyzed online such as in coronary intensive care monitoring, or long-term recordings are processed at speeds faster than real-time, as in Holter analysis. In both categories, a feature extraction stage detects waveforms, determines boundaries, examines morphology, computes amplitudes and duration, and measures interwave intervals. A contour-analysis stage applies clinical criteria to these measurements to arrive at a diagnostic classification. and a contextual string is then examined for rhythm analysis. This paper will describe the data acquisition and signal processing techniques that have been applied to computer-assisted electrocardiography since its advent in 1957. Methods for contour analysis and interval measurement will be described, and the application of diagnostic criteria to these results will be examined. Rhythm analysis and serial comparison. which are undergoing further development will be discussed. A historical review of the evolutionary stages of computerized electrocardiography will be presented leading to a discussion of the present state of the art and future trends. Rhythm analysis represents a particularly difficult aspect of computer interpretation. Because the QRS complex is the most easily detected waveform of the ECG, QRS morphology and RR interval measurements constitute the major features for rhythm determination in both the computer-assisted diagnostic ECG and computerized arrhythmia monitoring. Logic exists in most systems for P-wave information to be incorporated into the rhythm decision, but the frequent failure of P-wave detection represents a serious flaw in the accuracy of rhythm interpretation. New techniques for reliable P-wave measurements such as more optimally located electrodes. particularly those which hold promise for improved arrhythmia classification, will be presented. The problem of testing and evaluation of existing ECG systems continues to present difficulties and will be examined in light of recommendations that have been advanced. A library of tape recorded arrhythmias has been collected. diagnosed, and annotated by experts to serve as an instrument for the assessment of rhythm monitoring systems, but, to date, no such data exist for testing diagnostic systems.