Recovering heart sounds from sparse samples

Continuous monitoring of physiological functions such as heart sounds can pose severe constraints on data acquisition and processing systems, especially if remote monitoring is desired. In this paper, we investigate the utility of a recently proposed compressive sensing (CS) algorithm based on modulated discrete prolate spheroidal sequences (MDPSS) for recovering sparsely sampled heart sounds. In particular, we investigate the recordings containing opening snap (OS) or the third heart sounds (S3) in addition to first and second heart sounds. The results of numerical analysis show that heart sounds can be accurately reconstructed even when the sampling rate is reduced to 40% of the original sampling frequency.