DB-SMOTE及多层堆叠用于心律失常识别

doi:10.19665/j.issn1001-2400.2021.04.018

Abstract

Abstract:

In order to improve the recognition performance of the electrocardiogram,especially the recognition accuracy of minor diseases,this paper proposes the electrocardiogram recognition architecture based on the DB-SMOTE algorithm and multi-layered stacking model.The DB-SMOTE algorithm is proposed to solve the problem because the classical oversampling SMOTE algorithm ignores the intra-class unbalance of minority-class data.The new algorithm utilizes DBSCAN clustering to divide the data of minority classes into multiple clusters and filter out the noise samples,takes the boundary data of each cluster as the main body to generate new samples,and analyzes visually by tSNE.The performance of a single classifier cannot meet the requirements,so a multi-layered stack classification is used for identification,which is divided into two parts:the first is based on KNN,Xgboost and GBDT,and the feature F is mapped to F';the second part of the model is to identify the feature F'.This architecture has a 99.66% accuracy rate in identifying the electrocardiogram and can improve the recognition accuracy of minor diseases well,so it can be used to identify arrhythmias effectively.

Key words: electrocardiogram, DB-SMOTE, tSNE, stacking

CLC Number:

TP181

WANG Bo,DENG Ke. DB-SMOTE and multi-layer stacking used for Arrhythmia recognition[J].Journal of Xidian University, 2021, 48(4): 136-143.

Figures/Tables 12

References 17

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类别	N	LBBB	RBBB	PVC	APB
训练集	5 000	4 000	3 600	3 500	1 500+1 101
测试集	5 000	4 068	3 654	3 534	1 045

分类	正类	负类
正类	TP	FP
负类	FN	TN

参数	KNN	GBDT	Xgboost	KNN+DB-SMOTE	GBDT+DB-SMOTE	Xgboost+DB-SMOTE	多层堆叠
F-value	0.988 9	0.989 4	0.989 7	0.990 3	0.991 5	0.991 3	0.994 3
G-mean	0.988 7	0.989 7	0.988 6	0.990 4	0.991 6	0.991 6	0.994 4

文献	分类器方法	准确率/%
文中方法	多层分类器堆叠	99.66
文中深度学习方法1	VGG13网络	98.70
文中深度学习方法2	LSTM网络	99.08
FATIHA B^[14]方法	KNN	98.70
张异凡^[15]方法	LSTM;CNN	99.11
SHARMA M^[16]方法	小波分解;支持向量机	98.90
查雪帆^[17]方法	Alexnet	98.00

DB-SMOTE and multi-layer stacking used for Arrhythmia recognition

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References 17

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