Arrhythmia Classification Using Biased Dropout and Morphology-Rhythm Feature With Incremental Broad Learning

Arrhythmia Classification Using Biased Dropout and Morphology-Rhythm Feature With Incremental Broad Learning

In recent times, people have become increasingly health-conscious. To obtain timely and accurate information on the status of the heart, one of the most important organs of the human body, there is a growing demand among individuals and doctors for accurate and real-time automatic classification of...

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Bibliographic Details
Main Authors: Jia Li, Yang Zhang, Le Gao, Xiang Li
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Arrhythmia classification
biased dropout
broad learning
electrocardiogram
morphology-rhythm feature
Online Access:https://ieeexplore.ieee.org/document/9419050/

Internet

https://ieeexplore.ieee.org/document/9419050/

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