Abstract
This paper presents an attempt to decompose cardiac and respiratory signals from an electrical bioimpedance (EBI) dataset. To accomplish this task, the conventional filtering method is used. FIR (low pass filter (LPF) and high pass filter (HPF)) was intended to decompose the impedance respirogram (IRG) and impedance cardiogram (ICG), (the clean ECG was also extracted by filtering method). The decomposed components can be analysed and processed further, each one separately. Investigation was accomplished under the assumption that the total EBI dataset is the summation of cardiac and respiratory components, motion artefacts, stochastic disturbance and noise. The impedances were measured using a Zurich Instruments HF2IS Impedance Spectroscope. A sixteen electrodes configuration belt was used around a human thorax, to measure the EBI. This study showed that it is not possible to decompose cardiac and respiratory signals completely through conventional filtering method.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Mughal, Y.M. (2014). Decomposing of Cardiac and Respiratory Signals from Electrical Bio-impedance Data Using Filtering Method. In: Zhang, YT. (eds) The International Conference on Health Informatics. IFMBE Proceedings, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-319-03005-0_64
Download citation
DOI: https://doi.org/10.1007/978-3-319-03005-0_64
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03004-3
Online ISBN: 978-3-319-03005-0
eBook Packages: EngineeringEngineering (R0)