Arrhythmia Classifier using Binarized Convolutional Neural Network for Resource-Constrained Devices

@article{Wang2022ArrhythmiaCU,
  title={Arrhythmia Classifier using Binarized Convolutional Neural Network for Resource-Constrained Devices},
  author={Ao Wang and Wenxing Xu and Hanshi Sun and Ninghao Pu and Zijing Liu and Hao Liu},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.03661}
}
—Monitoring electrocardiogram signals is of great significance for the diagnosis of arrhythmias. In recent years, deep learning and convolutional neural networks have been widely used in the classification of cardiac arrhythmias. However, the existing neural network applied to ECG signal detection usually requires a lot of computing resources, which is not friendlyF to resource-constrained equipment, and it is difficult to realize real-time monitoring. In this paper, a binarized convolutional… 

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