A deep learning framework for electrocardiogram (ECG) super resolution and arrhythmia classification

Research on Biomedical Engineering Pub Date : 2024-02-24 DOI:10.1007/s42600-024-00343-w

Christina Perinbam Kaniraja, Vani Devi M, Deepak Mishra

引用次数: 0

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用于心电图（ECG）超分辨率和心律失常分类的深度学习框架

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Research on Biomedical Engineering Engineering-Biomedical Engineering

CiteScore

3.30

自引率

0.00%

发文量

期刊介绍： Research on Biomedical Engineering (ISSN Online 2446-4740; ISSN Print 2446-4732) is dedicated to publishing research in all fields of Biomedical Engineering. This multidisciplinary journal is aimed at readers and authors with an interest in using or developing tools based on the engineering and physical sciences to understand and solve problems in the biological and medical sciences. The journal is open to contributions in the following topics, including but not restricted to: Biomedical instrumentation, Biomechanics, Biorobotics, Rehabilitation engineering and assistive technologies, Applied engineering in neurology and neuroscience, Biomedical signal processing, Modelling of physiological systems, Cardiovascular and respiratory systems, Muscular and nervous systems, Use of laser, ultrasound and radiation in health, Medical imaging, Education and biomedical engineering, forensic, Clinical engineering, Metrology and biomedical engineering, Health technology, Health informatics and telemedicine, Biotechnology, Artificial organs, implants and biomaterials, Proteomics, genomics and bioinformatics.