Our general goal is automatic identification of arrhythmias within implantable devices by computer-based signal processing of the intracardiac electrograms. This goal appears to be realizable because: 1) the arrhythmias to be identified can be provoked in the catheter electrophysiology laboratory and the resulting electrograms can be recorded for detailed analysis; 2) modern signal processing techniques exist for characterizing the electrograms in the time domain and by spectral content; 3) computer algorithms can be designed to recognize these characteristic electrogram features in each arrhythmia; 4) implantable microcomputers are available in which the algorithms can be implemented. An important premise of this proposal is that the hardware for electrical termination of arrhythmia is already availbale and thus there is a risk of new generations of devices being implanted for arrhythmia control before the underlying electrophysiologic concepts and pattern recognition rules for identifying the arrhythmia are developed and tested. The signal processing algorithms and decision rules for automatic detection and discrimination will be implemented in real time in a computer program small enough to be part of an implanted anti-tachycardia or defibrillating device. We will first examine and describe in both the time and frequency domains the characteristic features of electrograms recorded during provocative electrophysiologic study in animals and humans. Then we will develop computer algorithms for signal processing of the electrograms and for arrhythmia pattern recognition. Finally, we will test the stated hypotheses by conducting additional animal and human electrophysiology studies and determining the sensitivity and specificity of the algorithms. Our approach combines the engineering skill of computer-based signal analysis with the medical skill of diagnostic cardiac electrophysiology. It is our expectation that this approach will provide a sound scientific basis upon which development of specific hardware by pacemaker manufacturers can proceed.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL035554-07
Application #
3349548
Study Section
Surgery, Anesthesiology and Trauma Study Section (SAT)
Project Start
1985-12-01
Project End
1994-03-31
Budget Start
1992-04-01
Budget End
1993-03-31
Support Year
7
Fiscal Year
1992
Total Cost
Indirect Cost
Name
Illinois Institute of Technology
Department
Type
Organized Research Units
DUNS #
City
Chicago
State
IL
Country
United States
Zip Code
60616
Polikaitis, A; Arzbaecher, R; Bump, T et al. (1997) Probability density function revisited: improved discrimination of VF using a cycle length corrected PDF. Pacing Clin Electrophysiol 20:1947-51
Polikaitis, A; Arzbaecher, R (1994) Sensitivity and specificity of a dual-chamber arrhythmia recognition algorithm for implantable devices. J Electrocardiol 27 Suppl:78-83
Throne, R; Wilber, D; Olshansky, B et al. (1993) Autoregressive modeling of epicardial electrograms during ventricular fibrillation. IEEE Trans Biomed Eng 40:379-86
Polikaitis, A; Arzbaecher, R (1992) Validation of an adaptive software trigger and arrhythmia diagnostic algorithm. J Electrocardiol 25 Suppl:173-7
Arzbaecher, R (1992) Automatic diagnosis of atrial fibrillation in implanted devices. J Electrocardiol 24 Suppl:134
Clarkson, P M; Fan, Q; Williamson, G A et al. (1992) Robust adaptive parameter estimators in arrhythmia detection. J Electrocardiol 25 Suppl:207-11
Throne, R D; Jenkins, J M; DiCarlo, L A (1991) A comparison of four new time-domain techniques for discriminating monomorphic ventricular tachycardia from sinus rhythm using ventricular waveform morphology. IEEE Trans Biomed Eng 38:561-70
Jadvar, H; Jenkins, J M; Stewart, R E et al. (1991) Computer analysis of the electrocardiogram during esophageal pacing cardiac stress. IEEE Trans Biomed Eng 38:1089-99
Bump, T E; Ripley, K L; Guezennec, A et al. (1989) The effect of drugs and lead maturation on atrial electrograms during sinus rhythm and atrial fibrillation. Am Heart J 117:577-84
Ripley, K L; Bump, T E; Arzbaecher, R C (1989) Evaluation of techniques for recognition of ventricular arrhythmias by implanted devices. IEEE Trans Biomed Eng 36:618-24

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