查看文章

The electrocardiogram (ECG) is a biophysical electric signal generated by the heart muscle, and is one of the major measurements of how well a heart functions. Automatic ECG analysis algorithms usually extract the geometric or frequency-domain features of the ECG signals and have already significantly facilitated automatic ECG-based cardiac disease diagnosis. We propose a novel ECG feature by fitting a given ECG signal with a 20th order polynomial function, defined as PolyECG-S. The PolyECG-S feature is almost identical to the fitted ECG curve, measured by the Akaike information criterion (AIC), and achieved a 94.4% accuracy in detecting the Myocardial Infarction (MI) on the test dataset. Currently ST segment elongation is one of the major ways to detect MI (ST-elevation myocardial infarction, STEMI). However, many ECG signals have weak or even undetectable ST segments. Since PolyECG-S does not …