An abundance of label-free microfluidic techniques for measuring cell intrinsic markers exists, yet these techniques are seldom combined because of integration complexity such as restricted physical space and incompatible modes of operation. We introduce a multiparameter intrinsic cytometry approach for the characterization of single cells that combines ≥2 label-free measurement techniques onto the same platform and uses cell tracking to associate the measured properties to cells. Our proof-of-concept implementation can measure up to five intrinsic properties including size, deformability, and polarizability at three frequencies. Each measurement module along with the integrated platform were validated and evaluated in the context of chemically induced changes in the actin cytoskeleton of cells. viSNE and machine learning classification were used to determine the orthogonality between and the contribution of the measured intrinsic markers for cell classification.