ECG-based heartbeat classification for arrhythmia detection: A survey

Highlights • Surveys the feature description methods, and the learning algorithms employed. • Also surveys the ECG signal preprocessing and the heartbeat segmentation techniques. • Description of databases used for methods evaluation indicated by the AAMI standard. • Discussion of limitations and dr...

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Bibliographic Details
Published in:	Computer methods and programs in biomedicine Vol. 127; pp. 144 - 164
Main Authors:	Luz, Eduardo José da S, Schwartz, William Robson, Cámara-Chávez, Guillermo, Menotti, David
Format:	Journal Article
Language:	English
Published:	Ireland Elsevier Ireland Ltd 01-04-2016
Subjects:	Abnormalities Algorithms Arrhythmias, Cardiac - diagnosis Arrhythmias, Cardiac - physiopathology Automation Classification ECG-based signal processing Electrocardiography Feature extraction Heart Heart diseases Heart Rate Heartbeat classification Heartbeat segmentation Humans Instrumentation Internal Medicine Learning algorithms Other Preprocessing Segmentation Surveys and Questionnaires Learning algorithms Feature extraction Preprocessing Heartbeat segmentation ECG-based signal processing Heartbeat classification
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Summary:	Highlights • Surveys the feature description methods, and the learning algorithms employed. • Also surveys the ECG signal preprocessing and the heartbeat segmentation techniques. • Description of databases used for methods evaluation indicated by the AAMI standard. • Discussion of limitations and drawbacks of the methods in the literature. • Concluding remarks and future challenges are also pointed out.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0169-2607 1872-7565
DOI:	10.1016/j.cmpb.2015.12.008