Laser Doppler flowmetry (LDF) technique is widely used in clinical investigations to monitor microvascular blood flow. It can be a very interesting tool to diagnose impairment in the microcirculation caused by pathologies. However, this can be done in an efficient way only if the processed signals are well understood. Therefore, in order to gain a better insight into LDF signals, this work presents numerically simulated data generated by a model based on nonlinear coupled oscillators. Linear and parametric couplings, as well as fluctuations are analyzed. Each simulated signal is processed to obtain its power spectrum in the frequency domain and a comparison with real data is proposed. The results show that the power spectra of the simulated signals reflect the presence of the cardiac, respiration, myogenic, neurogenic and endothelial related metabolic activities. However, their amplitude in the frequency domain are more pronounced than they are on real LDF signals. Moreover, the modeling of fluctuations is essential to reproduce the noise present on real data. Finally, linear couplings seem more adequate than parametric couplings to describe power spectra at frequencies higher than 1 Hz. This work will now serve as a basis to elaborate more powerful models of LDF data.