QRS detection method based on fully convolutional networks for capacitive electrocardiogram

作者：

Highlights：

• A deep learning based method for detecting QRS complexes.

• A fully convolutional network model with a large receptive field.

• A labeling process to generate ground-truth data.

• Postprocessing to improve the accuracy of QRS detection.

• Performance of the proposed method verified with real data.

摘要

•A deep learning based method for detecting QRS complexes.•A fully convolutional network model with a large receptive field.•A labeling process to generate ground-truth data.•Postprocessing to improve the accuracy of QRS detection.•Performance of the proposed method verified with real data.

论文关键词：Healthcare,Capacitive ECG,ECG beat detection,ECG segmentation,Deep learning,QRS complex

论文评审过程：Received 31 July 2018, Revised 2 April 2019, Accepted 23 May 2019, Available online 24 May 2019, Version of Record 5 June 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.05.033