Deterministic compressed sensing of heart sound signals

This paper proposes the use of the Deterministic Binary Block Diagonal (DBBD) matrix as sensing matrix for compressed sensing of heart sound signals. The use of a deterministic matrix has the advantage of not requiring the generation of random numbers in the acquisition node. Moreover, the DBBD matrix has a very low computational complexity at the compression side, as it only requires a sum of the samples. In the paper, the DBBD sensing matrix is used in combination with the Discrete Cosine Transform and the Mexican Hat wavelet to compress and reconstruct heart sound signal obtained from the PhysioNet database. The results show a lower value of the Percent Root Mean Square Difference compared to that obtained by the random sensing matrix previously used in the literature for heart sound signals.