Research Article
Research on ECG Classification Method Based on Convolutional Neural Network
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@INPROCEEDINGS{10.1007/978-3-031-04409-0_22, author={Jin Tao and Jianting Shi and Rongqiang Wu}, title={Research on ECG Classification Method Based on Convolutional Neural Network}, proceedings={Machine Learning and Intelligent Communications. 6th EAI International Conference, MLICOM 2021, Virtual Event, November 2021, Proceedings}, proceedings_a={MLICOM}, year={2022}, month={5}, keywords={Convolutional neural network Electrocardiogram Classification Convolution kernel scale}, doi={10.1007/978-3-031-04409-0_22} }- Jin Tao
Jianting Shi
Rongqiang Wu
Year: 2022
Research on ECG Classification Method Based on Convolutional Neural Network
MLICOM
Springer
DOI: 10.1007/978-3-031-04409-0_22
Abstract
The electrocardiogram reflects the temporal changes in the body’s cardiac potential; This is also an important technology for diagnosing cardiovascular disease, so the classification of electrocardiogram has gradually become the focus of many scholars. This paper designs an ECG classification algorithm based on convolutional neural network, which aims to automatically classify ECG using artificial intelligence algorithm. The algorithm has the characteristics of less parameters and more layers, and the classification speed is faster and has very strong real-time performance. The experimental results show that the accuracy of the algorithm reaches 98.1%, which has strong advantages in medical diagnosis and application.
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