Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 10
3016-3021

ECG signal classification based on combination of multifractal and its correlation features

Lu Qing
Li Qiusheng
Ye Lihua
Xu Depeng
School of Physics & Electronic Information, Gannan Normal University, Ganzhou Jiangxi 341000, China
DOI: 10.19734/j.issn.1001-3695.2023.02.0082

Abstract

The multifractal theory only performs statistical analysis on the singular exponents observed at any point on the geometric support of the fractal body. Multifractal correlation studies the spatial correlation characteristics between two points with different singular exponents. It is a generalization of single point statistics in multifractals. The two characteristics have a certain degree of complementarity. This paper investigated a method that combined the multifractal and its correlation features in the electrocardiogram(ECG) signal classification. Firstly, the method analyzed the multifractal and correlation characteristics of four types of ECG signals and obtained their respective features. Then it combined the probability distribution to select appropriate features for combination. The combined features fed into a support vector machine(SVM) for classification. This method tested on the MIT-BIH arrhythmia database and achieved an average accuracy of 97.90% after 20 training tests. Compared to independently using multifractal features, this method significantly improves the classification accuracy.

Foundation Support

江西省教育厅科技项目(190772)
江西省研究生创新专项基金项目(YC2021-S739)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.02.0082
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 10
Section: Algorithm Research & Explore
Pages: 3016-3021
Serial Number: 1001-3695(2023)10-020-3016-06

Publish History

[2023-05-09] Accepted Paper
[2023-10-05] Printed Article

Cite This Article

卢清, 李秋生, 叶莉华, 等. 基于多重分形及其关联特征组合的心电信号分类 [J]. 计算机应用研究, 2023, 40 (10): 3016-3021. (Lu Qing, Li Qiusheng, Ye Lihua, et al. ECG signal classification based on combination of multifractal and its correlation features [J]. Application Research of Computers, 2023, 40 (10): 3016-3021. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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