Blood is a dense suspension of soft non-Brownian cells of unique importance. Physiological blood flow involves complex
interactions of blood cells with each other and with the environment due to the combined effects of varying cell
concentration, cell morphology, cell rheology, and confinement. We analyze these interactions using computational
morphological image analysis and machine learning algorithms to quantify the non-equilibrium fluctuations of cellular
velocities in a minimal, quasi-two-dimensional microfluidic setting that enables high-resolution spatio-temporal
measurements of blood cell flow. In particular, we measure the effective hydrodynamic diffusivity of blood cells and
analyze its relationship to macroscopic properties such as bulk flow velocity and density. We also use the effective
suspension temperature to distinguish the flow of normal red blood cells and pathological sickled red blood cells and
suggest that this temperature may help to characterize the propensity for stasis in Virchow’s Triad of blood clotting and
thrombosis.