Janice M. Jenkins

A comparison of four new time-domain techniques for discriminating monomorphic ventricular tachycardia from sinus rhythm using ventricular waveform morphology

The authors have designed four new computationally efficient time-domain algorithms for distinguishing ventricular electrograms during monomorphic ventricular tachycardia (VT) from those during sinus rhythm using direct analysis of the ventricular electrogram morphology. All four techniques are independent of amplitude fluctuations and three of the four are independent of baseline changes. These new techniques were compared to correlation waveform analysis, a previously proposed method for distinction of VT from sinus rhythm. Evaluation of these four new algorithms was performed on data from 19 consecutive patients with 31 distinct monomorphic ventricular tachycardia morphologies. Three of the algorithms performed as well as or better than correlation waveform analysis but with one-tenth to one-half the computational demands.<<ETX>>

Identification of Ventricular Tachycardia Using Intracavitary Ventricular Electrograms: Analysis of Time and Frequency Domain Patterns

Tachycardia detection by implantable antitachycardia devices using rate alone has major limitations. Several alternative methods have been proposed to distinguish ventricular tachycardia or ventricular fibrillation from normal sinus rhythm using intracardiac electrograms. These methods have not been tested, however, for recognition of ventricular tachycardia in patients with abnormal surface QRS conduction during sinus rhythm or with antiarrhythmic drug therapy. In this study, three techniques for the indentification of ventricular tachycardia from intracavitary bipolar ventricular electrograms were examined and compared: correlation waveform analysis, amplitude distribution analysis, and spectral analysis using Fast Fourier transformation. Thirty episodes of induced monomorphic ventricular tachycardia were analyzed and compared sinus rhythm in four groups of patients with: I. Normal surface QRS conduction during sinus rhythm without antiarrhythmic drug therapy (five episodes); II. Intraventricular conduction delay or bundle branch block during sinus rhythm without antiarrhythmic drug therapy (nine episodes); III. Normal surface QRS conduction during sinus rhythm with antiarrhythmic therapy (six episodes); and IV. Intraventricular conduction delay or bundle branch block during sinus rhythm with antiarrhythmic drug therapy (ten episodes). Correlation waveform analysis had 100% sensitivity and specificity in distinguishing ventricular tachycardia from sinus rhythm, even in the presence of an intraventricular conduction delay, bundle branch block, and antiarrhythmic drug therapy. In contrast, amplitude distribution analysis differentiated 15/30 episodes (50.0%) of ventricular tachycardia from sinus rhythm, and a maximum of 18/30 episodes (60.0%) of ventricular tachycardia were identified by specal analysis using Fast Fourier transformation. Correlation waveform analysis appears to be a reliable technique to discriminate ventricular tachycardia from sinus rhythm using intracavitary ventricular electrograms. Its computational demands are modest, making it suitable for consideration in an implantable antitachycardia device.

Automatic Tachycardia Recognition

A microcomputer algorithm for tachycardia identification, suitable for use in un implanted antitachycardia pacemaker, is described. The system employs an atrial and ventricular electrogram, detects a sustained fast rate in either chamber, and awakens the main program to perform detailed analysis of the tachycardia and its immediately preceding beats. The algorithm distinguishes atrial, ventricular, and AV nodal and re‐entrant tachycardia from high rates due to sinus tachycardia. For testing of the program, we used a data base of twenty‐two tape‐recorded and documented arrhythmias provoked during electrophysiologic studies in which atrial and ventricular bipolar electrodes were in place; twenty‐one of twenty‐two wave successfully detected. These included atrial fibrillation, atrial flutter, atrial tachycardia, AV nodal re‐entrant tachycardia, AV re‐entrant tachycardia using an accessory pathway, and ventricular tachycardia with and without ventriculo‐atrial conduction.

Diagnosis of Atrial Fibrillation Using Electrograms from Chronic Leads: Evaluation of Computer Algorithms

This study compares the performance of three detection algorithms for the recognition of atrial fibrillation in chronic pacing leads. Multiple serial recordings were obtained of wideband and filtered electrograms from chronic atrial and ventricular leads in dogs for a period up to 55 days following implantation. Each dog was recorded in sinus rhythm and induced atrial fibrillation. Four days were chosen for processing: The day of implantation and a day in the first, second or third, and fifth weeks. Three signal processing methods were assessed for performance in detection of atrial fibrillation: software recognition of rate with automatic threshold control, amplitude distribution, and frequency spectral analysis. A software trigger for rate determination was adjusted to thresholds of 10, 20, and 30% of maximum baseline‐to‐peak amplitude. At 10%, a rate boundary anywhere between 420 and 560 beats per minute (bpm) perfectly separated atrial fibrillation from sinus rhythm even though atrial electrograms were contaminated with large QRS deflections and double‐sensing was present. At 20% and 30%, a rate boundary around 300 bpm could be used, but sensitivity and specificity were reduced to 90%. In amplitude distribution analysis, a percent of time within a baseline window provided perfect separation of atrial fibrillation from sinus rhythm. In all cases, the signal was within this window Jess than 43% of the time in atrial fibrillation, and more than 43% in sinus rhythm. In spectral analysis, frequency bands were examined for power content. In the 6 to 30 Hz band atrial fibrillation contained the greater power. Choosing 58% of total power as a discriminant, sensitivity and specificity of atrial fibrillation detection were 100% and 95% respectively.

Automatic computer processing of digital 2-dimensional echocardiograms.

Quantitative studies of left ventricular function using 2-dimensional echocardiography have been limited because of a lack of computerized methods to automatically analyze the echocardiographic images. Previous computer efforts have been directed at digitizing the video output of the 2-D echocardiogram, but this digitizing method has significant limitations. A direct digitization method that produces improvement in signal-to-noise ratio and, subsequently, improved automatic detection of endocardial and epicardial borders, was developed. With definition of these edges, left ventricular global and regional analysis is possible frame by frame so that dynamic changes in cardiac function may be assessed throughout the cardiac cycle. Further technologic advances in 2-D echocardiographic acquisition and image processing should allow computer processing of 2-D echocardiographic data in real time.

Discrimination of Retrograde from Anterograde Atrial Activation Using Intracardiac Electrogram Waveform Analysis

THRONE, R.D., et al.: Discrimination of Retrograde from Anterograde Atrial Activation Using Intracardiac Electrogram Waveform Analysis The prevention of pacemaker‐mediated tachycardias requires a safe, reliable method for distinguishing retrograde from anterograde atrial activation by dual chamber pacemakers. In this study, a technique was developed to detect the morphological change that occurs in the waveform of the intra‐atrial electrogram during retrograde atrial activation. The method employed for waveform analysis is based upon statistical correlation. In 19 patients undergoing electrophysiological studies, atrial electrograms were recorded from bipolar endocardial electrodes during sinus rhythm and 1:1 retrograde atrial depolarization while undergoing right ventricular pacing. Data were digitally sampled at 750, 1,000, and 1,500 Hz. Templates of anterograde atrial depolarization were constructed by signal averaging waveforms from an initial sinus rhythm passage. These were used for analysis of anterograde depolarizations from a subsequent passage of sinus rhythm and a passage of known retrograde atrial depolarization. In all 19 cases, a patient‐specific threshold could be derived to separate anterograde from retrograde atrial depolarizations using 1,000 Hz and 1,500 Hz sampling rates. However, at a sampling rate of 750 Hz, separation of anterograde from retrograde atrial activation was possible in only 16/19 patients (84%). We conclude that correlation waveform analysis of a suitably sampled atrial electrogram is a reliable method of discriminating retrograde atrial depolarization from anterograde atrial depolarization in intracardiac electrograms.

Detection algorithms in implantable cardioverter defibrillators

Presents a review of the evolution of tachycardia fibrillation detection algorithms designed for implantable cardioverter defibrillators (ICD) including those that have been incorporated into first, second, and third generation devices. The major emphasis of this review is an overview of the development of new and innovative means for improved detection in next-generation devices. Time-domain and frequency-domain methods of electrogram analyses are described, limitations are cited and promising new proposals for increased specificity which address the false shock incidence are presented.

Digital Signal Processing Chip Implementation for Detection and Analysis of Intracardiac Electrograms

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 realtime monitoring of electrophysiology studies or detection and classification of tachycardias in implantable antitachycardia devices.

Paroxysmal Bundle Branch Block of Supraventricular Origin: A Possible Source of Misdiagnosis in Detecting Ventricular Tachycardia Using Time Domain Analyses of Intraventricular Electrograms

Current implantable antitachycardia devices use several methods for differentiating sinus rhythm (SR)from Supraventricular tachycardia (SVT) or ventricular tachycardia (VT). These methods include sustained high rate, the rate of onset, changes in cycle length, and sudden onset. Additional methods for detecting VT include techniques based upon ventricular electrogram morphology. The morphological approach is based on the assumption that the direction of cardiac activation, as sensed by a bipolar electrode in the ventricle, is different when the patient is in SR as compared to VT. Whether paroxysmal bundle branch block of Supraventricular origin (BBB) can be differentiated from VT has not been determined. In this study, we compared the morphology of the ventricular electrogram during sinus rhythm with a normal QRS (SRNIQRS) or SVT with a normal QRS (SVTNIQRS) with the morphologies of BBB and VT in 30 patients undergoing cardiac electrophysiology studies. Changes in ventricular electrogram morphology were determined using three previously proposed time domain methods for VT detection: Correlation Waveform Analysis (CWA), Area of Difference (AD), and Amplitude Distribution Analysis (ADAJ. CWA, AD, and ADA distinguished VT from SRNIQRS or SVTNIQRS in 16/17 (94%), 14/57 (82%), and 12/17 (71%) patients, and BBB from SRNIQRS or SVTNIQRS in 15/15 (100%), 13/15 (87%), and 6/15 (40%) patients, respectively. However, the ranges of values during BBB using these methods overlapped with ranges of values during VT in all cases for CWA, AD, and ADA. Hence, BBB may be a source of misdiagnosis in detecting VT when these time domain methods are used for ventricular electrogram analysis.

Use of the pill electrode for transesophageal atrial pacing.

The pill electrode, which was developed for esophageal electrocardiography, has found application in transesophageal atrial pacing during procedures such as conversion of tachycardia, electrophysiologic measurement, and acceleration of heart rate to produce stress during cardiac imaging studies. This paper presents theoretical studies that examine the relationship of interelectrode distance, current level, and pulse duration to the achievement of successful capture. Theoretical results agree with our clinical findings, i.e., current levels of 25 mA are effective to sustain capture; increased pulse duration reduces current requirements; and close bipolar spacing combines efficacy with safety. Results of animal studies performed to assess the extent of esophageal burn injury reveal that current levels in excess of 75 mA are required to produce lesions in short‐term (under 30) minutes pacing, and greater than 60 mA in long‐term (4 hours) pacing. These results are based on experiments using a pulse duration of 2 ms, and the current levels that produce injury will be considerably lower if longer pulse durations are used. Typical current levels and pulse durations for successful capture are presented for 46 subjects in several new clinical applications. Termination of tachycardia, basic electrophysiologic measurements, and controlled acceleration of heart rate can be performed noninvasively with this technique.