The present work proposes the use of the Empirical Mode Decomposition (EMD) method conjointly with the Lomb-Scargle (LS) periodogram for the identification of Mayer waves (low-frequency oscillations in blood pressure). The EMD-LS method aims to overcome the limitations of the Fast Fourier Transform (which requires the signal to be periodically sampled), and to find the best pre-processing configuration to detect this waves in noisy signals and with data loss. The work also presents the obtained results with different combinations of Intrinsic Mode Functions (IMF) and shows that the combination of the average of IMF 1 and 2 achieved the highest detection accuracy (87.5%) on the calibration database. In addition, it demonstrates that the EMD-LS method was effective and did not show a significant difference in relation to the test using the complete database (even with the removal of 30% of the original data). It also highlights the importance of detecting those waves, which can provide relevant information about the patient’s condition and be used in testing models of the neural baroreflex system.