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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

ECG Annotation and Diagnosis Classification Techniques

verfasst von : Yan Yan, Xingbin Qin, Lei Wang

Erschienen in: Health Informatics Data Analysis

Verlag: Springer International Publishing

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Abstract

ECG annotation has been studied for decades for the development of signal processing techniques and artificial intelligence methods. In this chapter, the general technique roadmaps of ECG beat annotation (classification) are reviewed. The deep neuro network methods are introduced after the mention of supervised and unsupervised learning methods as well as the deep belief networks. A preliminary study on deep learning application in ECG classification is proposed in this chapter, which leads to better results and has a high potential both for performance improvement and unsupervised learning applications.

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Vorheriges Kapitel Biomedical Imaging Informatics for Diagnostic Imaging Marker Selection
Nächstes Kapitel EEG Visualization and Analysis Techniques
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Metadaten
Titel
ECG Annotation and Diagnosis Classification Techniques
verfasst von
Yan Yan
Xingbin Qin
Lei Wang
Copyright-Jahr
2017
Buch
Health Informatics Data Analysis

Print ISBN: 978-3-319-44979-1

Electronic ISBN: 978-3-319-44981-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-44981-4_9