纸质出版:2021
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林金朝, 李必禄, 李国权, 等. 基于EWT和结构特征提取的心电信号R波识别算法[J]. 电子学报, 2021,49(6):1217-1223.
林金朝, 李必禄, 李国权, et al. Recognition Algorithm of R Wave in ECG Based on EWT and Structure Feature Extraction[J]. Acta Electronica Sinica, 2021, 49(6): 1217-1223.
林金朝, 李必禄, 李国权, 等. 基于EWT和结构特征提取的心电信号R波识别算法[J]. 电子学报, 2021,49(6):1217-1223. DOI: 10.12263/DZXB.20200907.
林金朝, 李必禄, 李国权, et al. Recognition Algorithm of R Wave in ECG Based on EWT and Structure Feature Extraction[J]. Acta Electronica Sinica, 2021, 49(6): 1217-1223. DOI: 10.12263/DZXB.20200907.
R波作为心电信号中最明显的特征,常作为确定心电信号其他波段的重要依据.针对现有算法识别率低的问题,提出一种基于经验小波变换和信号结构特征的R波识别算法.首先利用经验小波变换对心电信号频谱进行自适应分割,在分割区间上构造合适的小波滤波器组提取出具有紧支撑的模态分量,然后对提取出的各模态分量进行频谱分析,找出R波对应的高频分量并对其进行结构分析,从而实现R波的准确定位.仿真结果表明,所提算法对心电信号R波识别的灵敏度达到99.93%,准确率达到了99.92%,阳性准确率达到99.99%,并且算法耗时仅0.68s,对R波具有很好的识别效果.
As the most obvious feature of electrocardiogram (ECG)
R wave is often used as an important basis to determine other bands of ECG. Aiming at the low recognition rate of existing algorithms
an R-wave recognition algorithm based on empirical wavelet transform and signal structure characteristics is proposed. Firstly
the empirical wavelet transform is used to adaptively segment the spectrum of ECG signal
and the appropriate wavelet filter banks are constructed in the segmentation interval to extract the tightly supported modal components. Then
the spectrum of each extracted modal component is analyzed to find out the corresponding high frequency component of R wave and analyze its structure
so as to realize the accurate positioning of R wave. The simulation results show that the sensitivity
accuracy and positive rate of the proposed algorithm for R-wave recognition of ECG signal are 99.93%
99.92% and 99.99% respectively
aand the algorithm takes only 0.68s with a good recognition effect for R-wave.
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