A Real-Time Cardiac Arrhythmia Classification Using Hybrid Combination of Delta Modulation, 1D-CNN and Blended LSTM
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
https://link.springer.com/content/pdf/10.1007/s11063-022-10949-9.pdf
Reference67 articles.
1. WHO (2019) New initiative launched to tackle cardiovascular disease, the world’s number one killer [Internet]
2. Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, Chiuve SE, Cushman M, Delling FN, Deo R et al (2018) Heart disease and stroke statistics2018 update: a report from the American Heart Association. Circulation 137(12):67–492
3. Yıldırım Ö, Pławiak P, Tan R-S, Acharya UR (2018) Arrhythmia detection using deep convolutional neural network with long duration ECG signals. Comput Biol Med 102:411–420
4. Yu S-N, Lee M-Y (2012) Bispectral analysis and genetic algorithm for congestive heart failure recognition based on heart rate variability. Comput Biol Med 42(8):816–825
5. Ionescu CM, Copot D (2017) Monitoring respiratory impedance by wearable sensor device: Protocol and methodology. Biomed Signal Process Control 36:57–62
Cited by 7 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. Enhanced ECG Signal features transformation to RGB matrix imaging for advanced deep learning classification of myocardial infarction and cardiac arrhythmia;Multimedia Tools and Applications;2024-05-13
2. Automated cardiac arrhythmia detection techniques: a comprehensive review for prospective approach;Computer Methods in Biomechanics and Biomedical Engineering;2024-04-02
3. Video-based HR measurement using adaptive facial regions with multiple color spaces;Biocybernetics and Biomedical Engineering;2024-01
4. Boruta Feature Selection Method for Optimizing a Case-Based Reasoning Model to Predict Heart Disease;International Journal of Pattern Recognition and Artificial Intelligence;2023-11
5. Cardiac arrhythmia detection from ECG signal using Siamese adversarial neural network;Multimedia Tools and Applications;2023-10-12
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3