Overview of CARMEM: A new dynamic quantitative cardiac model for ECG monitoring and its adaptation to observed signals

Different approaches have been proposed in order to achieve knowledge integ ration for coronary care monitoring applications, usually in the form of ex pert systems. The clinical impact of these expert systems, which are based only on "shallow" knowledge, has not been remarkable due to the difficultie s associated with the construction and maintenance of a complete knowledge base. Model-based systems represent an alternative to these problems becaus e they allow efficient integration of the "deep" knowledge on the underlyin g physiological phenomena being monitored. In this work, a brief review of existing model-based systems for cardiac rhythm interpretation is presented , followed by the description of a new system for Cardiac Arrhythmia Recogn ition by Model-Based ECG Matching (CARMEM). Fundamental characteristics of CARMEM are presented; in particular, its ability to provide online paramete r adaptation to simulate complex rhythms and to match observed ECG signals. The proposed model can be useful for the explanation of the origin of card iac arrhythmias and contribute towards their robust characterization in the context of coronary care units.