Testing of Sparse Domains and Gradient-based Reconstruction Algorithm on 1D Biomedical Signals: Student paper

The main interest of this paper is concept of Compressive Sensing and its application in 1D biomedical signals. The accent is on analyzing several types of biomedical signals and finding domain in which they are sparse. Therefore, we use gradient-based algorithm to reconstruct these biomedical signals with different number of samples. By working with gradient-based algorithm, we presented reconstruction of Electrocardiogram, Electroencephalogram and Electromyogram biomedical signals and drew a conclusion about differences between them. Several sparsifying basis are tested in order to find the most suitable one, for specific signal type, and we verified the whole theory by experimental results.