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Detection of Acute Ischemia Episodes from QRS Angles Changes using a Laplacian Noise Model
2014
International Conference on Computing in Cardiology
Ischemia detectors represent a useful diagnosis tool to identify acute ischemic episodes in coronary artery disease patients. In this paper, a detector of acute ischemic events based on the analysis of the QRS angles is presented. This acute ischemia detector has been developed by modelling the ischemia-induced changes in the QRS angles as an abrupt change with a certain transition time, assuming a Laplacian noise-model. The standard 12-lead electrocardiogram was used to test the proposed
dblp:conf/cinc/PerezMLP14
fatcat:43qmscpo5ncntc5nshnrlb4rcu