Technology of Graphic & Image
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940-943

Study on classification algorithm of arrhythmia signals based on machine learning

Liu Teng1
Tang Hong2
Zhang Shibing1,2
1. School of Electronics & Information, Nantong University, Nantong Jiangsu 226019, China
2. Nantong Research Institute for Advanced Communication Technologies, Nantong Jiangsu 226019, China

Abstract

Based on the data files provided by the MIT-BIH, this paper extracted the characteristic information of ECG signals by wavelet transform, and studied the classification and recognition of common signals. This paper mainly designed and implemented three classification algorithms based on softmax regression and neural network. Simulation experiments show that the training speed of a suitable neural network algorithm is faster. With fewer iterations, the accuracy rate of classification recognition is more than 90%.

Foundation Support

江苏省高等学校自然科学研究重大项目(17KJA540001)
南通大学—南通智能信息技术联合研究中心开放课题(KFKT2017B07)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0545
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 3
Section: Technology of Graphic & Image
Pages: 940-943
Serial Number: 1001-3695(2020)03-067-0940-04

Publish History

[2020-03-05] Printed Article

Cite This Article

刘腾, 唐虹, 张士兵. 基于机器学习的心律失常信号分类算法研究 [J]. 计算机应用研究, 2020, 37 (3): 940-943. (Liu Teng, Tang Hong, Zhang Shibing. Study on classification algorithm of arrhythmia signals based on machine learning [J]. Application Research of Computers, 2020, 37 (3): 940-943. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
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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.

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