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ECG MIT-BIH Data Analysis and Modelling

ECG Arrhythmia CNN Conv1D Neural Network
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This is also the ECG dataset from Kaggle, put together from PhysioNet MIT-BIH Arrhythmia (https://www.kaggle.com/shayanfazeli/heartbeat). This dataset is pre-processed with beats recorded in a 10 second window and is classified in 5 categories: 0.0 : Normal Heartbeat 1.0 : Atrial premature 2.0 : Premature ventricular contraction 3.0 : Fusion of ventricular and normal 4.0 : Unclassifiable For more details, please read the paper at (https://arxiv.org/pdf/1805.00794.pdf). In this workflow Conv1D Neural Network is trained for the classification task. The network implemented is a small version of what is described in the paper. Read more about this workflow here: https://www.knime.com/blog/ecg-categorization-to-detect-arrhythmia

External resources

  • ECG Heartbeat Classification: A Deep Transferable
  • Kaggle Dataset

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