Automatic QRS complex detection using two-level convolutional neural network.

Journal: Biomedical engineering online
Published Date: Jan 29, 2018

Abstract

BACKGROUND: The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and parameters, which may introduce significant computational complexity, especially in the transform domains. In addition, fixed features and parameters are not suitable for detecting various kinds of QRS complexes under different circumstances.

Authors

  • Yande Xiang
    College of Information Science and Electronic Engineering, Zhejiang University, Zheda Road 38, Hangzhou, 310027, China.
  • Zhitao Lin
    Institute of VLSI Design, Zhejiang University, Zheda Road 38, Hangzhou, 310027, China.
  • Jianyi Meng
    State Key Laboratory of ASIC and System, Fudan University, Zhangheng Road 825, Shanghai, 201203, China. mengjy@fudan.edu.cn.

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