[1]姚远星,王飞,刘文涵,等.基于多分支融合神经网络的心电图导联重构方法[J].中国医学物理学杂志,2023,40(2):196-201.[doi:DOI:10.3969/j.issn.1005-202X.2023.02.012]
　YAO Yuanxing,WANG Fei,LIU Wenhan,et al.ECG signal reconstruction based on multi-layer feature fusion using neural network[J].Chinese Journal of Medical Physics,2023,40(2):196-201.[doi:DOI:10.3969/j.issn.1005-202X.2023.02.012]
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基于多分支融合神经网络的心电图导联重构方法()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
40卷
期数:
2023年第2期
页码:
196-201
栏目:
医学信号处理与医学仪器
出版日期:
2023-03-03

文章信息/Info

Title:
ECG signal reconstruction based on multi-layer feature fusion using neural network
文章编号:
1005-202X（2023）02-0196-06
作者:
姚远星; 王飞; 刘文涵; 何进; 王豪; 常胜; 黄启俊
武汉大学物理科学与技术学院， 湖北 武汉 430072
Author(s):
YAO Yuanxing;  WANG Fei;  LIU Wenhan;  HE Jin;  WANG Hao;  CHANG Sheng;  HUANG Qijun
School of Physics and Technology, Wuhan University, Wuhan 430072, China
关键词:
心电图; 心电图重构; 卷积神经网络; 双向长短期记忆网络
Keywords:
electrocardiogram electrocardiogram signal reconstruction convolutional neural network bidirectional long short-term memory
分类号:
R318；R540.41
DOI:
DOI:10.3969/j.issn.1005-202X.2023.02.012
文献标志码:
A
摘要:
设计一种新型的多分支信息融合神经网络结构，利用已知的I，II，V2 3个导联心电信号来重构其它导联心电信号。基于卷积神经网络结构提取多个导联的特征然后进行线性相加融合，采用一种改进的双向长短期记忆网络结构来获得与时序相关的信息，从而实现心电图导联重构。使用Physikalisch Technische Bundesanstalt（PTB）数据库进行验证，导联重构方法具有0.944 4的相关系数和0.320 3的均方根误差，说明新型神经网络结构可以有效地实现心电图导联重构。
Abstract:
A novel neural network which can achieve multi-layer feature fusion is proposed for reconstructing the electrocardiogram (ECG) signals of other leads using the known ECG signals of leads I, II and V2. The features of multiple leads are extracted by convolutional neural network for linear combination, and an improved bidirectional long short-term memory network structure is used to obtain temporal sequence correlation which is then fused with the features obtained by convolutional neural network for realizing ECG signal reconstruction. The proposed method is verified with Physikalisch Technische Bundesanstalt database. The results show that the signal reconstruction method has a correlation coefficient of 0.944 4 and a low root-mean-square error of 0.320 3, which demonstrates the effectiveness of the novel neural network structure for ECG signal reconstruction.

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备注/Memo

备注/Memo:
【收稿日期】2022-10-18 【基金项目】国家自然科学基金（81971702, 61874079, 61574102, 61774113） 【作者简介】姚远星，硕士研究生，研究方向：医学信号处理，E-mail: 616195877@qq.com 【通信作者】黄启俊，教授，研究方向：医学信号处理及微电子系统设计，E-mail: huangqj@whu.edu.cn
更新日期/Last Update: 2023-03-03