Arrhythmia Disease Diagnosis Based on ECG Time–Frequency Domain Fusion and Convolutional Neural Network

Author:

Wang Bocheng1ORCID,Chen Guorong1ORCID,Rong Lu1,Liu Yuchuan1ORCID,Yu Anning1ORCID,He Xiaohui2,Wen Tingting1,Zhang Yixuan1,Hu Biaobiao1

Affiliation:

1. School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China

2. Chongqing Vocational Institute of Engineering, Chongqing, China

Funder

Chongqing Special Key Project for Technology Innovation and Application Development

Chongqing Municipal Education Commission Science and Technology Research Project

Chongqing University of Science and Technology Research Funding Projects

Natural Science Foundation of Chongqing

Open Foundation of the Chongqing Key Laboratory for Oil and Gas Production Safety and Risk Control

Cooperation projects between universities in Chongqing and the Chinese Academy of Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Medicine

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sensor-Enhanced Deep Learning for ECG Arrhythmia Detection: Integrating Multiscale Convolutional and Self-Attentive GRU Networks;IEEE Sensors Journal;2024-09-01

2. RHYTHMI: A Deep Learning-Based Mobile ECG Device for Heart Disease Prediction;Applied System Innovation;2024-08-29

3. Development of a Deep Learning Model for the Prediction of Ventilator Weaning;International Journal of Online and Biomedical Engineering (iJOE);2024-08-08

4. A Comprehensive Ensemble Machine Learning Model for Predicting Parkinson’s Disease Progression and Severity;2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI);2024-03-14

5. A Secure and Robust ECG Signal Transmission System for Cardiac Arrhythmia Identification;2024 International Conference on Computing, Networking and Communications (ICNC);2024-02-19

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