Heart Beat Classification Method based on Random Forest Algorithm

An interpatient classification method using the second lead for the Association for the Advancement of Medical Instrumentation (AAMI) standard is introduced. This study includes three parts. In the first part, the fuzzy matching algorithm is used to locate the key waveform points of Electrocardiogram (ECG) data. In the second part, the feature engineering algorithm is used to filter the extracted data sets. In the third part, the random forest model is carried out to realize the five classifications of heart disease by the selected features. The final precision, recall, and F1-score are 91%, 89%, and 90%, respectively.