In this study, a distributed approach to account for dynamic friction during needle insertion in soft tissue is presented. As is well known, friction is a complex nonlinear phenomenon. It appears that classical or static models are unable to capture some of the observations made in systems subjected to significant frictional effects. In needle insertion, translational friction would be a matter of importance when the needle is very flexible, or a stop-and-rotate motion profile at low insertion velocities is implemented, and thus, the system is repeatedly transitioned from a pre-sliding to a sliding mode and vice versa. In order to characterize friction components, a distributed version of the LuGre model in the state-space representation is adopted. This method also facilitates estimating cutting force in an intra-operative manner. To evaluate the performance of the proposed family of friction models, experiments were conducted on homogeneous artificial phantoms and animal tissue. The results illustrate that our approach enables us to represent the main features of friction which is a major force component in needle-tissue interaction during needle-based interventions.