title: A parallel implementation of a multi-state Kalman filtering algorithm to detect ECG arrhythmias.
abstract: Detecting arrhythmias from the electrocardiogram (ECG) is of great importance for the continued development of intelligent cardiovascular monitors (ICM). An ICM's main goal is to present to the clinician a 'high-level' analysis of the patient's condition (e.g., the patient is slightly hypovolemic) based upon 'low-level' physiologic signals (e.g., blood pressure, heart rate, etc.). This paper reports on a parallel implementation of a multi-state Kalman filtering algorithm, within a prototype ICM, to help detect ECG arrhythmias. Preliminary test results show that the parallel, multi-state implementation performed exactly as the original sequential version. Several different rhythm disturbances were correctly identified after 3-5 beats. We conclude that our parallel implementation of the multi-state Kalman filter provides a faster and still reliable means of accurately detecting ECG arrhythmias in real-time.
authors.affiliation: Department of Anesthesiology, Yale University School of Medicine, New Haven, CT 06510.
authors.forename: D F
authors.initials: DF
authors.lastname: Sittig
authors.forename: K H
authors.initials: KH
authors.lastname: Cheung
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D002319:Cardiovascular System / Q000503:physiopathology; D003936:Diagnosis, Computer-Assisted; D004562:Electrocardiography; D006801:Humans; D008954:Models, Biological; D008991:Monitoring, Physiologic; D012984:Software