Automatic classification of atrial fibrillation from short single-lead ECG recordings using a Hybrid Approach of Dual Support Vector Machine

作者：

Highlights：

• Hybrid Approach of Dual Support Vector Machine is used for the detection of AFr.

• Cardiac segmentation was used to further evaluate and diagnose AFr based on the ECG.

• A comparative study is made on detection of AFr using the top five-scoring methods.

• The proposed algorithm saves the operation time in addition to improving accuracy.

摘要

•Hybrid Approach of Dual Support Vector Machine is used for the detection of AFr.•Cardiac segmentation was used to further evaluate and diagnose AFr based on the ECG.•A comparative study is made on detection of AFr using the top five-scoring methods.•The proposed algorithm saves the operation time in addition to improving accuracy.

论文关键词：Atrial fibrillation (AFr),Cardiac arrythmia (CA),Dual Support Vector Machine (DSVM),Hybrid Approach (HA)

论文评审过程：Received 28 June 2021, Revised 4 March 2022, Accepted 6 March 2022, Available online 10 March 2022, Version of Record 19 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116848