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Volume 7, Issue 1
Adaptive Filtering and Characteristics Extraction for Impedance Cardiography

Xinyu Hu, Xianxiang Chen, Ren Ren, Bing Zhou, Yangmin Qian, Huaiyong Li & Shanhong Xia

Journal of Fiber Bioengineering & Informatics, 7 (2014), pp. 81-90.

Published online: 2014-07

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  • Abstract
Impedance Cardiography (ICG) is a noninvasive technique for monitoring stroke volume, cardiac output and other hemodynamic parameters, which is based on sensing the change of thoracic electrical impedance caused by blood volume change in aorta during the cardiac cycle. Motion artifact and respiratory artifact can lead to baseline drift in ICG signal, particularly during or after exercise, which can cause errors when calculating hemodynamic parameters. This paper presents an LMS-based adaptive filtering algorithm to suppress the respiratory artifact of ICG signal without restricting patients' breath. Estimation of hemodynamic parameters requires error-free automatic extraction of the characteristic points. Wavelet transform is used for extracting characteristic points which include its peak point (Z), start point (B) and end point (X) of left ventricular ejection time.
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@Article{JFBI-7-81, author = {}, title = {Adaptive Filtering and Characteristics Extraction for Impedance Cardiography}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2014}, volume = {7}, number = {1}, pages = {81--90}, abstract = {Impedance Cardiography (ICG) is a noninvasive technique for monitoring stroke volume, cardiac output and other hemodynamic parameters, which is based on sensing the change of thoracic electrical impedance caused by blood volume change in aorta during the cardiac cycle. Motion artifact and respiratory artifact can lead to baseline drift in ICG signal, particularly during or after exercise, which can cause errors when calculating hemodynamic parameters. This paper presents an LMS-based adaptive filtering algorithm to suppress the respiratory artifact of ICG signal without restricting patients' breath. Estimation of hemodynamic parameters requires error-free automatic extraction of the characteristic points. Wavelet transform is used for extracting characteristic points which include its peak point (Z), start point (B) and end point (X) of left ventricular ejection time.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbi03201407}, url = {http://global-sci.org/intro/article_detail/jfbi/4768.html} }
TY - JOUR T1 - Adaptive Filtering and Characteristics Extraction for Impedance Cardiography JO - Journal of Fiber Bioengineering and Informatics VL - 1 SP - 81 EP - 90 PY - 2014 DA - 2014/07 SN - 7 DO - http://doi.org/10.3993/jfbi03201407 UR - https://global-sci.org/intro/article_detail/jfbi/4768.html KW - Impedance Cardiography KW - Adaptive Filtering KW - Wavelet Transform KW - Characteristic Points KW - Hemodynamic Indices KW - Respiratory Artifact AB - Impedance Cardiography (ICG) is a noninvasive technique for monitoring stroke volume, cardiac output and other hemodynamic parameters, which is based on sensing the change of thoracic electrical impedance caused by blood volume change in aorta during the cardiac cycle. Motion artifact and respiratory artifact can lead to baseline drift in ICG signal, particularly during or after exercise, which can cause errors when calculating hemodynamic parameters. This paper presents an LMS-based adaptive filtering algorithm to suppress the respiratory artifact of ICG signal without restricting patients' breath. Estimation of hemodynamic parameters requires error-free automatic extraction of the characteristic points. Wavelet transform is used for extracting characteristic points which include its peak point (Z), start point (B) and end point (X) of left ventricular ejection time.
Xinyu Hu, Xianxiang Chen, Ren Ren, Bing Zhou, Yangmin Qian, Huaiyong Li & Shanhong Xia. (2019). Adaptive Filtering and Characteristics Extraction for Impedance Cardiography. Journal of Fiber Bioengineering and Informatics. 7 (1). 81-90. doi:10.3993/jfbi03201407
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