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.<
>