ecg_cnn_mit

ECG MIT-BIH Data Analysis and Modelling

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 heartbeats 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