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The importance of mucosal wave detection and estimation has been stressed in literature regarding the automatic classification and recognition of larynx pathologies from voice records. Using a new estimation method of the mucosal wave correlate and simulation results from a 2-mass model of the vocal folds the present paper shows that the main fingerprints found in the power spectral density of the mucosal wave correlate are directly related to the biomechanics of the system. These findings open the door to the non-invasive estimation of biomechanical parameters of the vocal folds directly from voice records, thus easing the task of automatic pathologic classification and recognition.