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Please use this identifier to cite or link to this item: http://idr.iitbbs.ac.in/jspui/handle/2008/1957
Title: A Review of Signal Processing Techniques for Electrocardiogram Signal Quality Assessment
Authors: Satija U.
Ramkumar B.
Sabarimalai Manikandan M.
Keywords: ECG noise
Electrocardiogram (ECG)
signal quality assessment
signal quality index
Issue Date: 2018
Citation: 11
Abstract: Electrocardiogram (ECG) signal quality assessment (SQA) plays a vital role in significantly improving the diagnostic accuracy and reliability of unsupervised ECG analysis systems. In practice, the ECG signal is often corrupted with different kinds of noises and artifacts. Therefore, numerous SQA methods were presented based on the ECG signal and/or noise features and the machine learning classifiers and/or heuristic decision rules. This paper presents an overview of current state-of-the-art SQA methods and highlights the practical limitations of the existing SQA methods. Based upon past and our studies, it is noticed that a lightweight ECG noise analysis framework is highly demanded for real-time detection, localization, and classification of single and combined ECG noises within the context of wearable ECG monitoring devices which are often resource constrained. � 2008-2011 IEEE.
URI: http://dx.doi.org/10.1109/RBME.2018.2810957
http://10.10.32.48:8080/jspui/handle/2008/1957
Appears in Collections:Research Publications

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