Title :
A stochastic network model of the interaction between cardiac rhythm and artificial pacemaker
Author :
Greenhut, Saul E. ; Jenkins, Janice M. ; MacDonald, Robert S.
Author_Institution :
Telectronics Pacing Syst. Inc., Englewood, CO, USA
Abstract :
In order to study heart-pacemaker interaction (HPI), a computer model of the cardiac conduction system has been developed which includes the effects of artificial pacemaker function and failure. The stochastic network model of cardiac conduction consists of five vertices, each representing a functional electrophysiologic element. Electrophysiologic multidimensional conditional probability functions determine the depolarization status of each vertex. The atrioventricular (AV) node is emulated using a mathematical model which includes the influence of past cycle lengths on AV nodal conduction time. Twenty-three classes of arrhythmias may be simulated and, for pacing simulation, one of 12 antibradycardia pacing modes may be chosen. Random effects of pacemaker malfunction including oversensing, undersensing, or failure-to-capture may be simulated through the use of probability distribution functions. This model should prove useful in the development of pacemaker algorithms, determining patient-specific pacemaker therapy, and predicting causes for apparent pacemaker malfunction. The model has been used in the development of an expert system to analyze paced ECGs for pacemaker function and malfunction.
Keywords :
electrocardiography; medical expert systems; medical signal processing; pacemakers; physiological models; probability; stochastic processes; antibradycardia pacing modes; arrhythmias; artificial pacemaker function; atrioventricular node; cardiac conduction system; cardiac rhythm; computer model; depolarization status; expert system; failure-to-capture; functional electrophysiologic element; heart-pacemaker interaction; multidimensional conditional probability functions; nodal conduction time; oversensing; paced ECGs; pacemaker algorithms; pacing simulation; past cycle lengths; patient-specific pacemaker therapy; probability distribution functions; signal flow network; stochastic network model; undersensing; Electrocardiography; Expert systems; Mathematical model; Medical treatment; Multidimensional systems; Pacemakers; Predictive models; Probability distribution; Rhythm; Stochastic processes; Algorithms; Arrhythmias, Cardiac; Computer Simulation; Electrocardiography; Equipment Design; Equipment Failure; Expert Systems; Heart Conduction System; Heart Rate; Humans; Models, Cardiovascular; Pacemaker, Artificial; Stochastic Processes;
Journal_Title :
Biomedical Engineering, IEEE Transactions on