Symposium on Cardiac Rhythm Disturbances II

Computers for Recognition and Management of Arrhythmias Harry Fozzard, MD.,* and Plato Kinias, M.S.**

In ever increasing ways computers are being employed in medicine to provide the doctor and the patient with special services. Two specific applications of these machines to cardiac care are intensive care monitoring and outpatient detection of arrhythmias. A number of systems are now commercially available and are being taken from the research context into direct patient care. These systems show much promise for improving care of the cardiac patient, but their properties are outside the traditional knowledge and experience of the practicing physician. In this chapter we will discuss computerized detection of arrhythmias and its clinical values. We will also review the characteristics of some of the available systems to assist in selecting the appropriate ones for hospital and laboratory use. The Clinical Problem Disorders of cardiac rhythm are common and are responsible for a significant part of the morbidity and mortality of cardiac disease. Some relationships are well documented and the clinical meaning of the abnormal rhythm is clear. On the other hand, there is major uncertainty in the minds of physicians today regarding the importance of certain rhythms, such as premature ventricular beats, and their optimal mode of treatment. Intermittent atrial tachyarrhythmias represent a source of inconvenience to the patient and frustration for the physician. Typically the patient's rhythm is normal on visit to the office, but he describes "spells" consistent with periods of atrial fibrillation or flutter or paroxysmal atrial tachycardia. Hospitalization for rhythm monitoring is expensive "'Professor of Medicine and Physiology, University of Chicago Pritzker School of Medicine; Joint Chief of Cardiology, University of Chicago Hospitals and Clinics; Director, Biomedical Computer Facility, Chicago, Illinois "n"Research Associate (Instructor), Biomedical Computer Facility, University of Chicago, Chicago, Illinois Supported in part by USPHS Myocardial Infarction Research Unit Contract N01-HV81334 and HL17648 SCOR·IHD.

Medical Clinics of North America- VoL 60, No. 2, March 1976




and inconvenient as a way of identifying the rhythms that may be the basis of the spells. Further the circumstances are sufficiently different in the hospital that the rhythm responsible for the "spells" may not occur. Portable tape recorders for sampling of 10 to 24 hour segments of the patient's electrocardiogram under reasonably normal activity is a valuable way to obtain proof of the abnormal rhythm and to correlate it with symptoms. The anlysis of the tape is, however, a tiresome and unquantitative task. Repeated tape recordings to monitor effectiveness of therapy are rarely done because of the expense and inconvenience of the test. Heart block or abnormally slow pacemaker activity may also be intermittent and associated with transient symptoms. Again, long-term tape recording is a reasonable diagnostic tool, but analysis is tedious. Ventricular tachyarrhythmias are potentially lethal, and can be implicated in the occurrence of "sudden death," a major cause of death in the United States. 9 Detection and quantitation of these ventricular rhythms is difficult in inpatients and outpatients, although the long-term tape recording is much more sensitive than the standard electrocardiogram because of the intermittent nature of the rhythmY The graded exercise test often is associated with ventricular arrhythmias in patients with coronary heart disease. Ryan et alY compared the incidence of arrhythmias provoked by the exercise test to those detected on 24-hour tape recording and found the tape recording to reveal a higher incidence. An additional disadvantage of the exercise test is that correlation of the abnormal rhythm with symptoms is more difficult. Presuming that the physician finds a way to recognize the patient with a high risk of ventricular arrhythmia, he has the task of choosing therapy and monitoring it. It would be difficult to train sufficient technicians to read the large number of Holter tapes required to accomplish this. Inpatient monitoring for rhythm abnormalities has been fairly successful in the coronary care unit because of highly trained nursing personnel. Yet they have difficulty giving quantitative reports, and evaluation of the additive effects of several antiarrhythmic agents is uncertain and unreliable. Monitoring in the hospital outside of special intensive care units can be quite inadequate, depending on the number and training of general nursing personnel. In summary, detection of arrhythmias and monitoring of therapeutic effectiveness is a difficult task, and accurate automatic monitoring devices could represent a significant benefit to the patient and his physician.

The Computer as a Rhythm Monitor The first attempts to determine rhythm by computer were as part of the diagnostic programs for routine electrocardiogram reading. 20 Most of these efforts had limited success because no more than ten cycles were available in a particular electrocardiogram lead. More recently advantage was taken of simultaneous multiple lead analysis by the Bonner program,2 with good PVC detection. The attempt to achieve real-time analysis of rhythm in clinical



monitoring units such as the coronary care unit has led to three major approaches. One approach identifies a "normal" QRS and compares subsequent beats for variation." The second, represented by our AZTEC system,4 extracts features of the QRS for comparison with a generalized normal pattern. The third approach utilizes a combined analog and digital system to detecting and identifying abnormalities in the QRS.12 The stored normal method allows automatic accumulation of an averaged "typical" cycle, or selection of a "normal" cycle by an observer. Abnormal cycles are identified by comparison of each cycle with the stored one by cross-correlation or by simpler properties such as area or equivalent function. This method is quite sensitive to abnormalities, but has difficulty with fusion cycles and may generate large numbers of falsely abnormal indications if the patient's QRS changes much. Some of these systems allow automatic adaptation to a new "normal;" others must be updated by an observer. For cross-correlation a fair amount of computation is required, slowing the analysis. Feature extraction is an attempt to identify the components of the QRS and certain simple properties such as "area." These are compared with a generalized normal that is intended to be valid for all conditions for the patient and probably for all patients. Grouping of abnormalities into different "families" allows expansion of the normal range and grading of the abnormalities into many subcategories. Hybrid systems employ some amount of analog cycle detection. A typical approach is for R waves to be detected by a voltage threshold on the voltage signal, on its first derivative, or on a combination of values above threshold. This approach also permits substantial filtering of the signal to avoid interference from muscle noise, but this occasionally results in muscle noise being smoothed to resemble a QRS. Sometimes the analog phase simply leads to selective digital sampling of the electrocardiogram, but in other cases abnormal cycles are immediately detected. Most systems employ timing information as expected. For tachyarrhythmias the rate is a significant factor. In PVC detection, the amount of prematurity required is often a critical factor, since it leads to errors in detecting fusion beats. No real-time system appears to detect P waves in a reliable fashion, so the analysis is restricted to QRS shape and timing information to determine rhythm. In an attempt to solve the problem of P wave detection, Rey et al.16 obtained an atrial electrogram directly from an intra-atrial lead introduced through a peripheral vein. Quantitative data to validate the comparative accuracy and sources of error in these approaches has been scanty. An attempt to tabulate the published information is found in Table 1. In general, each approach has its drawbacks, related to the use of a single lead, to problems with muscle noise, and to the need to draw inference from QRS information only. The information in Tables 1 and 2 was extracted primarily from the proceedings of a conference entitled "Computers in Cardiology" held in Bethesda, Maryland in October 1974. We cannot claim that the information is complete, and no attempt was made to obtain unpublished information.


Signal amplitude

RR interval


PDP-9 PDP-15



Feature extraction, probability


Edinburgh (Surgery)

Signal amplitude


Edinburgh (MedPhysics)

80'* 0.04,* beats

90'* 0.07% beats

0.4(Yr beats


PVC detection


Arrhythmia events 70% False positive alarms about 17% of true positive

Arrhythmia events 99% False positive alarms about 15% of true positives

PVC detection False positive

Stored normal, area difference


Worchester Poly technical Institute

Signal amplitude QRS thresholds



University of Chicago

Stored normal, cross correlation



PVC detection False positive QRS duration


Signal amplitude Aztec aperture


Feature extraction

Feature extraction


PVC detection False positive




Signal amplitude




Washington University



Real Time Rhythm Monitors


Table 1.







"tl t-< ;»




;» :



;;:: 'tI ..,c::




Table 2.

Faster than Real Time Rhythm Monitors NUMBER


Washington University U .S. Air Force Edinburgh Stanford Cardio Dynamics


System 7 and special purpose hardware Hybrid Hybrid PDP-12 and special purpose hardware Special purpose







PVC detection 89%

1 2

60X 60X 60X

Inadequate PVC detection 96% PVC detection 98%





With the increasing use of taped electrocardiographic data from, for example, Holter recorders, there has been attention to automated systems that can analyze the electrocardiogram faster than real-time. Most of these are based on concepts developed for real-time systems,3. 13, 19 but with greater emphasis on analog or hard-wired digital processing.6 ,B,13 Several experimental systems now run at 60 times real time, although multiple playings of the tape may be required. An attempt to tabulate the reported results in this area is seen in Table 2. Agreed approaches to quality control are less developed in this area than in real-time monitoring, so that comparisons are less informative than in Table 1. Altogether, it now seems clear that most workers have begun to profit from each other's experience and development is proceeding in only a few directions. As one would expect, any effort to increase the sensitivity of the detection scheme to guarantee fewer missed abnormal cycles results inevitably in increased false positives. In addition, benefits can be found by adjustment of recognition parameters to fit the normal and abnormal QRS patterns of a given patient, but this requires greater operator training and interaction. As systems mature, they seem to develop more hard-wired digital or analog components, so that the eventual result is likely to be hybrid. Although there are many problems yet to be solved, it is apparent that analysis at 30 to 60 times real-time with minimal operator interaction is feasible and will probably be achieved in the next few years. Future development may involve use of multiple leads and of sampling strategies not yet considered by clinicians. Clinical Studies Using Computerized Rhythm Detection Only a few examples of the use of computerized rhythm systems for clinical studies can be found. We reported the accuracy of nurses' diagnosis of arrhythmia events in the coronary care unit. 7 Oliver et al,15 examined the types of ventricular arrhythmias that occurred in patients after hospitalization for acute myocardial infarction. The same group has also analyzed responsiveness of PVC's to various antiarrhythmic drugs. 14 Talbot and his colleagues have used their system for evaluation of the influence of a new antiarrhythmic agent. IS Bernard et al. 1 report



use of their system for measurement of PVC suppression by drugs. Mantle et aUo adapted the AZTEC System to monitor beat-by-beat changes in rhythm in patients with acute myocardial infarction, illustrating changes in rate prior to the onset of pain in unstable angina. The promise of these computerized systems for clinical research has been discussed frequently, and is undoubtedly valid. Nevertheless, the developers of these tools must consider their success quite limited until there is substantial use of the rhythm monitors in clinical research or patient care.

The Future Directions in this developmental area are dictated by both clinical needs and technological changes. The advent of integrated circuits and microcomputers means that cardiac monitors may reach the size and cost of pocket calculators in a few years. At that time, both the lower cost and increased convenience of the monitors will contribute to their widespread use in hospitals and in outpatients. There seems to be no technical impediment in the way of providing a reliable pocket rhythm monitor for patients considered to be at high risk. Research uses of rhythm detection systems are likely to focus on the problem of sudden death. This work is directed to identification of premonitory electrical events in individual patients. If it is successful, then the same techniques will be employed in testing the effectiveness of various drugs in modifying the occurrence of consequences of the abnormal electrical events. REFERENCES 1. Bernard, R, Rey, W., Vainsel, H., et al.: Computerized dysrhythmia monitoring with an intra-auricular lead. Proceedings, Conference on Computers in Cardiology. Bethesda, Maryland, 1974. 2. Bonner, R. E., Crevasse, L., Ferrer, M. 1., et al.: A new computer program for analysis of scale electrocardiograms. Comput. Biomed. Res., 5:629-653,1972. 3. Clark, K. W., Nolle, F. M., Cox, J. R, Jr.: High performance computer programs for rapid analysis of long ECG records. Proceedings, San Diego Biomedical Symposium, 1974. 4. Cox, .J. R, .Jr., Fozzard, H. A., Nolle, F. M., et al.: Some data transformations useful in electrocardiography. In Stacy, R W., and Waxman, B. D., eds.: Computers in Biomedical Research. New York, Academic Press, Vol. 3, 1969. 5. Feldman, C. L., Hubelbank, M., and Amazeen, P. G.: A real time ectopic heart beat detection system. Proceedings of 21st Annual Conference of Engineering Medicine and Biology, Houston, Texas, 1968. 6. Fitzgerald, J. W., Clappier, R W., and Harrison, D. C.: Small computer processing of ambulatory electrocardiograms. Proceedings, Conference on Computers in Cardiology. Bethesda, Maryland, 1974. 7. Fozzard, H. A., and Kinias, P.: ECG Monitoring: a review of developmental systems. Proceedings, Conference on Computers in Cardiology. Bethesda, Maryland, 1974. 8. Hansmann, D. R: High speed rhythm and morphological analysis of continuous ECG recordings. Proceedings, Conference on Computers in Cardiology. Bethesda, Maryland, 1974. 9. Kotler, M. N., Tabtznik, B., Mower, M. M., et al.: Prognostic significance of ventricular ectopic beats with respect to sudden death in the late postinfarction period. Circulation, 47:959-966, 1973. 10. Mantle, J. A., Strand, E. M., James, T. N., et al.: Changes in cardiac electrical stability in unstable ischemic heart disease. Circulation, 50:II1-96, 1974.



11. Moss, A, J., Schnitzler, R., Green, R., et al.: Ventricular arrhythmias three weeks after acute myocardial infarction. Ann. Intern. Med., 75:837-841, 1971. 12. Neilson, J. M.: An adaptive arrhythmia monitor. Proceedings, Conference on Computers in Cardiology. Bethesda, Maryland, 1974. 13. Neilson, J. M.: High speed analysis of ventricular arrhythmias from 24 hour recordings. Proceedings, Conference on Computers in Cardiology. Bethesda, Maryland, 1974. 14. Oliver, G. C., Kleiger, R. E., Krone, R. J., et al.: Application of high speed analysis of ambulatory electrocardiograms. Proceedings, Conference on Computers in Cardiology. Bethesda, Maryland, 1974. 15. Oliver, G. C., Nolle, F. M., Tiefenbrunn, A. J., et al.: Ventricular arrhythmias associated with sudden death in survivors of acute myocardial infarction. Amer. J. Cardiol., 33:160,1974. 16. Rey, W., Laird, J., and Hugenholtz, P.: P-wave detection by digital computer. Comput. Biomed. Res., 4:509-522, 1971. 17. Ryan, M., Lown, B., and Horn, H.: Comparison of ventricular ectopic activity during 24hour monitoring and exercise testing in patients with coronary heart disease. New Eng. J. Med., 292:224-229, 1975. 18. Talbot, R. G., Nimmo, J., Julian, D. G., et aL: Treatment of ventricular arrhythmias with Mexiletine (Ko 1173) Lancet, 2:399-403, 1973. 19. Waiter, W. H., Grassman, E. D., Engelken, E. J., et al.: Dynamic electrocardiography and computer analysis. Aerospace Med., 44 :414-417, 1973. 20. Wortzman, D., Gilmore, B., Schwetman, H. D., et al.: A hybrid computer system for the measurement and interpretation of electrocardiograms. Ann. N.Y. Acad. Sci., 128:876899, 1966. Biomedical Computer Facility University of Chicago Pritzker School of Medicine 950 East 59th Street Chicago, Illinois 60615

Computers for recognition and management of arrhythmias.

Symposium on Cardiac Rhythm Disturbances II Computers for Recognition and Management of Arrhythmias Harry Fozzard, MD.,* and Plato Kinias, M.S.** In...
677KB Sizes 0 Downloads 0 Views