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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Bibliographic Details
Published in:	IEEE sensors journal Vol. 20; no. 5; pp. 2578 - 2589
Main Authors:	Thakkar, Hiren Kumar, Sahoo, Prasan Kumar
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.03.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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 Access:	Get full text
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