A multicriteria decision based approach for ischaemia detection in long duration ECGs

A new method based on a multicriteria classification algorithm, which is applied on data extracted from the electrocardiographic signal and the patient's history, is described for the detection of ischaemic episodes in long duration electrocardiographic recordings. The classification procedure is embedded into a four-stage system of automated ischaemia diagnosis. Using a task-specific cardiac beat database the multicriteria method was properly adjusted to classify each presented cardiac beat as ischaemic or normal. The method was tested using the cardiac beat database and we achieved good results, equal or even better than other reported methods, demonstrating the efficiency of the proposed methodology.