Heartbeat classification by random forest with a novel context feature: a segment label

HIGHLIGHTS

• who: Congyu Zou et al. from the In the last decade, many studies utilized machine learning to classify heartbeatsThose machine learning based classifiers are mostly trained with features from the following two categories:, . medical features [3, ], such as pre rr, post rr, local rr, global rr, etc. and, . statistic features in the field of signal processing [3, , ], such as higher-order statistics, wavelet transform coefficients, entropy, and energy density, etc. Besides those two categories, some studies proposed their novel features, such as Sparse Representation [6]. Regarding feature selection, methods like principal component analysis [7], Mutual Information (MI . . .
  

   

  

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