MATHEMATICAL MODELS OF COMPLEX CARDIAC ARRHYTHMIAS

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Individuals with arrhythmia in which abnormal heartbeats are interspersed with normal heartbeats may be at high risk for sudden cardiac death. This work is focused towards analyzing and modeling electrocardiographic data collected over a 24 hour period in patients with frequent ventricular ectopy. We visualize the statistical properties of the abnormal heartbeats in 'heart-prints' that show characteristic patterns for each patient and may give information about the underlying mechanisms. These patterns should be reproduced by a simulation of an appropriate nonlinear model. We are investigating models in which abnormal heartbeats are generated randomly, are generated at a fixed time interval following a preceding normal heartbeat, or are generated by an independent oscillator that may or may not interact with the normal heartbeat. Although, we have found that it is difficult to reproduce all the statistical features of the records using these simple models, in one case there is close correspondence between the model and a wide range of statistical features of the data. We are analyzing Holter recordings of patients who have experienced sudden cardiac death in order to characterize the statistical patterns of activity prior to the arrest. This work draws attention to the complex rhythms of the heart, and introduces methods that can be used to classify them.