摘要
为快速准确地检测出心电信号中的QRS波群,提出一种基于残差网络(ResNet)与双向长短期记忆网络(BiLSTM)的深度学习模型—ResBiLSTM,检测QRS波群的起始点和终点。实验结果表明:相比于传统的QRS波群检测方法,ResBiLSTM提高了检测效率,且具有较强的鲁棒性,能够准确检测不同形态的QRS波群。
In order to detect QRS complexes quickly and accurately,a deep learning model based on residual network(ResNet)and bidirectional long short-term memory network(BiLSTM)is proposed and the model is ResBiLSTM.The ResBiLSTM can detect the start and end points of QRS complexes.The experimental results show that compared with the traditional QRS complexes detection methods,ResBiLSTM not only improves the detection efficiency,but also has strong robustness,which can accurately detect different forms of QRS complexes.
作者
黄毅
孙为军
王丹雷
伍贤美
袁永浩
Huang Yi;Sun Weijun;Wang Danlei;Wu Xianmei;Yuan Yonghao(Guangdong University of Technology,Guangzhou 510006,China)
出处
《自动化与信息工程》
2021年第1期22-26,48,共6页
Automation & Information Engineering
关键词
心电信号
QRS波群
残差网络
双向长短期记忆网络
electrocardiogram
QRS complexes
residual network
bidirectional long short-term memory
