Automated classification of five arrhythmias and normal sinus rhythm based on RR interval signals

作者：

Highlights：

• Automated arrhythmia detection with high accuracy.

• Residual Neural Network for time series data classification.

• Six class problem: five arrhythmias and normal.

• RR intervals: Convenient data acquisition and cost efficient data handling.

• Algorithmic foundation for smart m-health applications.

摘要

•Automated arrhythmia detection with high accuracy.•Residual Neural Network for time series data classification.•Six class problem: five arrhythmias and normal.•RR intervals: Convenient data acquisition and cost efficient data handling.•Algorithmic foundation for smart m-health applications.

论文关键词：Computer aided diagnosis,Arrhythmia detection,Deep learning,Residual Neural Network,M-health

论文评审过程：Received 1 November 2020, Revised 12 March 2021, Accepted 9 April 2021, Available online 20 April 2021, Version of Record 16 May 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115031