Adaptive Filtering and Characteristics Extraction for Impedance Cardiography (Journal of Fiber Bioengineering and Informatics, 2014)
Impedance Cardiography (ICG) is a noninvasive technique for monitoring stroke volume, cardiac outputand other hemodynamic parameters, which is based on sensing the change of thoracic electrical impedancecaused by blood volume change in aorta during the cardiac cycle. Motion artifact and respiratory artifactcan lead to baseline drift in ICG signal, particularly during or after exercise, which can cause errors whencalculating hemodynamic parameters. This paper presents an LMS-based adaptive filtering algorithmto suppress the respiratory artifact of ICG signal without restricting patients' breath. Estimation ofhemodynamic parameters requires error-free automatic extraction of the characteristic points. Wavelettransform is used for extracting characteristic points which include its peak point (Z), start point (B)and end point (X) of left ventricular ejection time.