Automatic diagnosis of cardiovascular disorders by sub images of the ECG signal using multi-feature extraction methods and randomized neural network-Reference-Cited by-同舟云学术

Automatic diagnosis of cardiovascular disorders by sub images of the ECG signal using multi-feature extraction methods and randomized neural network

Published:2021-02 Issue: Volume:64 Page:102260
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Ertuğrul Ömer Faruk,Acar Emrullah^ORCID,Aldemir Erdoğan,Öztekin Abdulkerim

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference71 articles.

1. Recommendations for the Standardization and Interpretation of the Electrocardiogram

2. Recommendations for the Standardization and Interpretation of the Electrocardiogram

3. Mobile wearable device for long term monitoring of vital signs;Klingeberg;Comput. Methods Programs Biomed.,2012

4. Fog computing in healthcare internet of things: a case study on ecg feature extraction;Gia;2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing,2015

5. Health fog: a novel framework for health and wellness applications;Ahmad;J. Supercomput.,2016

Cited by 20 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. A Novel Hybrid Vision Transformer CNN for COVID-19 Detection from ECG Images;Computers;2024-04-23

2. An efficient wavelet thresholding strategy and robust shrinkage approach for de‐noising ECG signal;International Journal of Imaging Systems and Technology;2023-12-28

3. Design of low-noise low-power ECG amplifier circuit with high integration level;Journal of Physics: Conference Series;2023-11-01

4. Machine learning based hybrid anomaly detection technique for automatic diagnosis of cardiovascular diseases using cardiac sympathetic nerve activity and electrocardiogram;Biomedical Engineering / Biomedizinische Technik;2023-10-12

5. A Systematic Review of Machine Learning and IoT Applied to the Prediction and Monitoring of Cardiovascular Diseases;Healthcare;2023-08-09