Towards Automatic and Fast Annotation of Seismocardiogram Signals Using Machine Learning

The automatic annotation of Seismocardiogram (SCG) potentially aid to estimate various cardiac health parameters continuously. However, the inter-subject variability of SCG poses great difficulties to automate its accurate annotation. The objective of the research is to design SCG peak retrieval met...

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Veröffentlicht in:	IEEE sensors journal Jg. 20; H. 5; S. 2578 - 2589
Hauptverfasser:	Thakkar, Hiren Kumar, Sahoo, Prasan Kumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Abnormalities Annotations automatic annotation cardiac health parameters (CHPs) Electrocardiography Estimation Feature extraction Heart rate variability Machine learning Morphology non-invasive Parameter estimation Performance evaluation Response time Seismocardiogram (SCG) Sensors State-of-the-art reviews Support vector machines Valves
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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