title: Quantitative analysis of cardiac arrhythmias.
abstract: Quantitative analysis of cardiac arrhythmias has been the subject of intensive research during the last 10 years. Several systems have been designed to help in the processing of cardiac signals: single or multiple lead electrocardiograms (ECG), electrograms from intracardiac catheters, esophageal recordings, etc. The main objective of these developments was oriented toward positive identification of arrhythmias or rhythm-disturbance counts to imitate the cardiologist's interpretation in contexts such as routing ECG and ambulatory recordings. However, these systems were mainly measurement tools aimed at extracting auricular and ventricular depolarization timings plus gross morphology description. The domain of morphology analysis of beat-to-beat auricular depolarization on ECG has never been highly active due to poor signal conditions. For routine ECG, automatic interpretation was set as an objective to complement computer-assisted ECG interpretation of conduction problems (i.e., morphology analysis of a representative beat extracted or averaged from the dominant rhythm). The limitations of rhythm interpretation in this context are well known. In the ambulatory ECG context, the analysis procedures are relatively simple and are often summarized as trivial counts describing, most exclusively, the ventricular arrhythmic behavior of the heart over a relatively long duration. Waveform-detection and measurement have been the bottleneck of advancement in arrhythmia analysis since highly reliable detection of events on a beat-to-beat basis are necessary to perform a valid analysis. Rare approaches have proposed probabilistic definition of event detection. The present review puts emphasis on the potential of several methods which have been demonstrated as powerful in identifying short- or long-duration heartbeat patterns, mode of heartbeat initiation, mode of heartbeat coupling, etc. Globally, these methods are referred to as time series analysis, modeling of rhythm patterns, simulation, and pattern recognition. A delay in the advancement of the study of arrhythmogenesis and limiting the analysis of arrhythmias to textbook descriptions is not justified when put in perspective of the potential of implementing powerful techniques which have been more or less neglected or used in a narrow way.
mesh_terms: D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000503:physiopathology; D001698:Biomedical Engineering; D001699:Biometry; D003201:Computers; D003936:Diagnosis, Computer-Assisted; D004562:Electrocardiography / Q000379:methods; D004594:Electrophysiology; D006801:Humans; D008955:Models, Cardiovascular; D008991:Monitoring, Physiologic; D013997:Time Factors