基于互信息的多导联心电图排序方法

doi:10.16180/j.cnki.issn1007-7820.2024.02.008

Abstract

Abstract:

The studies of automatic Electrocardiograph(ECG) classification based on convolutional neural networks all extract features from the ECG with the default 12-lead sequence, ignore the influence of lead sequence on feature extraction of convolutional network. To solve the problem, this study proposes a 2-end increasing sorting method based on mutual information, which uses mutual information to measure the correlation between leads. According to the correlation between leads and the characteristics of two-dimensional convolution, the adjacent connections of closely related leads are sorted.The experimental results show that the multi-lead ECG sorting method has achieved remarkable results on three databases and three convolutional network classification models.F1, accuracy, recall, accuracy, and Jacquard's coefficient of the proposed method increases by 0.011,0.009,0.007,0.014, and 0.013, while Hamming's loss decreases by 0.002.

Key words: electrocardiogram, arrhythmia, convolutional neural network, mutual information, multi lead, sorting, classification, correlation

CLC Number:

TN183

NAN Jiao,SUN Zhanquan. Sorting Method of Multi Leads ECG Based on Mutual Information[J].Electronic Science and Technology, 2024, 37(2): 55-60.

Figures/Tables 8

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References 18

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模型	排序方法	A_p	H_p	J_p	R_p	P_p	F1
VGGNet	默认排序	0.727	0.043	0.673	0.853	0.761	0.804
	两端递增排序	0.727	0.042	0.681	0.853	0.771	0.810
	两端递减排序	0.699	0.045	0.659	0.841	0.752	0.794
	类最大树排序	0.724	0.042	0.680	0.854	0.769	0.809
GoogLeNet	默认排序	0.749	0.044	0.683	0.841	0.781	0.809
	两端递增排序	0.758	0.041	0.696	0.848	0.795	0.820
	两端递减排序	0.717	0.044	0.669	0.853	0.755	0.802
	类最大树排序	0.749	0.043	0.682	0.829	0.794	0.811
ResNet	默认排序	0.729	0.042	0.678	0.854	0.767	0.808
	两端递增排序	0.728	0.042	0.681	0.859	0.766	0.810
	两端递减排序	0.742	0.044	0.673	0.831	0.779	0.804
	类最大树排序	0.728	0.042	0.680	0.866	0.759	0.809

模型	排序方法	A_p	H_p	J_p	R_p	P_p	F1
VGGNet	默认排序	0.709	0.012	0.743	0.876	0.831	0.853
	两端递增排序	0.741	0.011	0.756	0.903	0.823	0.861
	两端递减排序	0.710	0.012	0.738	0.881	0.819	0.849
	类最大树排序	0.718	0.012	0.748	0.880	0.832	0.855
GoogLeNet	默认排序	0.725	0.011	0.759	0.880	0.847	0.863
	两端递增排序	0.738	0.011	0.767	0.888	0.849	0.868
	两端递减排序	0.724	0.012	0.755	0.874	0.847	0.860
	类最大树排序	0.726	0.011	0.759	0.876	0.850	0.863
ResNet	默认排序	0.727	0.011	0.750	0.887	0.832	0.859
	两端递增排序	0.735	0.011	0.761	0.894	0.836	0.864
	两端递减排序	0.719	0.012	0.748	0.883	0.830	0.855
	类最大树排序	0.724	0.011	0.758	0.877	0.847	0.862

模型	排序方法	A_p	H_p	J_p	R_p	P_p	F1
VGGNet	默认排序	0.325	0.024	0.496	0.724	0.612	0.663
	两端递增排序	0.325	0.024	0.501	0.704	0.635	0.668
	两端递减排序	0.333	0.024	0.499	0.702	0.633	0.665
	类最大树排序	0.316	0.024	0.493	0.717	0.613	0.661
GoogLeNet	默认排序	0.345	0.023	0.516	0.715	0.650	0.681
	两端递增排序	0.357	0.022	0.522	0.745	0.636	0.686
	两端递减排序	0.336	0.022	0.513	0.757	0.614	0.678
	类最大树排序	0.344	0.023	0.515	0.735	0.632	0.680
ResNet	默认排序	0.352	0.023	0.514	0.740	0.628	0.679
	两端递增排序	0.354	0.023	0.517	0.737	0.634	0.682
	两端递减排序	0.331	0.023	0.509	0.725	0.631	0.675
	类最大树排序	0.347	0.023	0.515	0.726	0.639	0.680

模型	排序方法	A_p	H_p	J_p	R_p	P_p	F1
VGGNet	互信息	0.727	0.042	0.681	0.853	0.771	0.810
	欧式距离	0.717	0.044	0.667	0.854	0.752	0.800
	余弦相似度	0.711	0.044	0.665	0.848	0.755	0.799
	相关系数	0.721	0.043	0.672	0.851	0.762	0.804
GoogLeNet	互信息	0.758	0.041	0.696	0.848	0.795	0.820
	欧式距离	0.744	0.043	0.681	0.839	0.783	0.810
	余弦相似度	0.728	0.042	0.681	0.859	0.766	0.810
	相关系数	0.729	0.044	0.670	0.835	0.773	0.803
ResNet	互信息	0.728	0.042	0.681	0.859	0.766	0.810
	欧式距离	0.742	0.044	0.673	0.831	0.779	0.804
	余弦相似度	0.735	0.043	0.677	0.851	0.768	0.807
	相关系数	0.716	0.044	0.669	0.836	0.769	0.801

模型	排序方法	A_p	H_p	J_p	R_p	P_p	F1
VGGNet	互信息	0.741	0.011	0.756	0.903	0.823	0.861
	欧式距离	0.679	0.013	0.735	0.846	0.848	0.847
	余弦相似度	0.713	0.012	0.747	0.883	0.828	0.855
	相关系数	0.714	0.012	0.744	0.874	0.832	0.853
GoogLeNet	互信息	0.738	0.011	0.767	0.888	0.849	0.868
	欧式距离	0.724	0.011	0.758	0.881	0.844	0.862
	余弦相似度	0.708	0.012	0.747	0.846	0.865	0.855
	相关系数	0.724	0.012	0.755	0.874	0.850	0.861
ResNet	互信息	0.735	0.011	0.761	0.894	0.836	0.864
	欧式距离	0.724	0.011	0.752	0.886	0.832	0.859
	余弦相似度	0.714	0.012	0.743	0.900	0.809	0.852
	相关系数	0.730	0.011	0.755	0.886	0.836	0.861

Sorting Method of Multi Leads ECG Based on Mutual Information

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