  The paper analyses the possibility to recover different biomedical signals if
limited number of samples is available. Having in mind that monitoring of
health condition is done by measuring and observing key parameters such as
heart activity through electrocardiogram or anatomy and body processes through
magnetic resonance imaging, it is important to keep the quality of the
reconstructed signal as better as possible. To recover the signal from limited
set of available coefficients, the Compressive Sensing approach and
optimization algorithms are used. The theory is verified by the experimental
results.
