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This paper is an attempt to separate cardiac and respiratory signals from anelectrical bio-impedance (EBI) dataset. For this two well-known algorithms,namely Principal Component Analysis (PCA) and Independent Component Analysis(ICA), were used to accomplish the task. The ability of the PCA and the ICAmethods first reduces the dimension and attempt to separate the usefulcomponents of the EBI, the cardiac and respiratory ones accordingly. It wasinvestigated with an assumption, that no motion artefacts are present. To carryout this procedure the two channel complex EBI measurements were provided usingclassical Kelvin type four electrode configurations for the each complexchannel. Thus four real signals were used as inputs for the PCA and fast ICA.The results showed, that neither PCA nor ICA nor combination of them can notaccurately separate the components at least are used only two complex (fourreal valued) input components.

Separation of cardiac and respiratory components from the electrical bio-impedance signal using PCA and fast ICA