A parallel implementation of a multi-state Kalman filtering algorithm to detect ECG arrhythmias

Detecting arrhythmias from the electrocardiogram (ECG) is of vital importance for the continued development of an intelligent cardiovascular monitor (ICM). The ICM´s main goal is to present to the clinician a high-level analysis of the patient´s condition based upon low-level physiologic signals (e.g., blood pressure, heart rate, etc.). The authors report on the parallel implementation of a multi-state Kalman filtering algorithm, within the prototype ICM, to help detect ECG arrhythmias. Preliminary test results show that the parallel, multi-state implementation performed exactly as the original sequential version. Rhythm disturbances of all modeled types were correctly identified after 3-5 beats. The authors conclude that the parallel implementation of the multi-state Kalman filter provides a faster, yet reliable, means of accurately detecting ECG arrhythmias in real time