A knowledge-based technique for automated detection of ischaemic episodes in long duration electrocardiograms |
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Authors: | C Papaloukas Dr D I Fotiadis A P Liavas A Likas L K Michalis |
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Institution: | Department of Medical Physics, Medical School, University of Ioannina, Greece. |
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Abstract: | A novel method for the detection of ischaemic episodes in long duration ECGs is proposed. It includes noise handling, feature extraction, rule-based beat classification, sliding window classification and ischaemic episode identification, all integrated in a four-stage procedure. It can be executed in real time and is able to provide explanations for the diagnostic decisions obtained. The method was tested on the ESC ST-T database and high scores were obtained for both sensitivity and positive predictive accuracy (93.8% and 78.5% respectively using aggregate gross statistics, and 90.7% and 80.7% using aggregate average statistics). |
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Keywords: | Ischaemic episodes detection Knowledge-based method ECG noise handling |
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