Detection of sleep apnea using Machine learning algorithms based on ECG Signals: A comprehensive systematic review

作者：

Highlights：

• Diagnosis of sleep apnea based on ECG characteristics is very accurate.

• Diagnosis of sleep apnea with electrocardiogram can replace the present methods.

• SVM and Neural Network algorithms were highly accurate.

• Frequency and time domain features were the most commonly used features.

摘要

•Diagnosis of sleep apnea based on ECG characteristics is very accurate.•Diagnosis of sleep apnea with electrocardiogram can replace the present methods.•SVM and Neural Network algorithms were highly accurate.•Frequency and time domain features were the most commonly used features.

论文关键词：Sleep Apnea,Machine Learning,Polysomnography,Electrocardiogram,Accuracy,Systematic Review

论文评审过程：Received 20 March 2021, Revised 8 July 2021, Accepted 19 September 2021, Available online 25 September 2021, Version of Record 30 September 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115950