Sparse Reconstruction Method for Separating Cardiac and Respiratory Components from Electrical Bioimpedance Measurements
In this work, we investigate the possibility of employing sparse reconstruction framework for the separation of cardiac and respiratory signal components from the bioimpedance measurements. The signal decomposition is complicated by the nonstationarity of the signal and overlapping of their spectra. The signal has a harmonic structure, which is sparse in the spectral domain. We approach the problem by considering a dictionary with integrated wideband elements describing spectral components of the considered signal. The parameter estimation task is solved by the means of sparse reconstruction where solving the optimization problem returns a sparse vector of relevant dictionary atoms.