Acute MI Detection Derived From ECG Parameters Distribution

Alfonso Aranda, Pietro Bonizzi, Joel Karel, Ralf Peeters
2019 2019 Computing in Cardiology Conference (CinC)   unpublished
Several studies in the past have evaluated the use of different ECG-based features to diagnose acute myocardial infarction (AMI). This was generally done by looking at how well a feature reflects differences between baseline (no AMI) and AMI situations. This approach tends to overlook the progress of AMI and to underestimate false positives when implemented into a continuous monitoring setting and therefore appears inadequate for it. This has hindered the adoption of those methods in the
more » ... l practice. In this research, we present a novel set of parameters for the dynamic assessment of AMI condition. Those parameters are obtained by analyzing the changes over time in the distribution properties of ECG-based features.
doi:10.22489/cinc.2019.337 fatcat:h5yts4tcgzb3ffn7snhxliuwbu