A Novel Force Modeling Scheme for Needle Insertion Using Multiple Kalman Filters

Abstract

In this paper, the interaction force between a surgical needle and soft tissue is studied. The force is modeled using a novel nonlinear dynamic model. Encouraged by the LuGre model for representing friction forces, the proposed model captures all stages of needle-tissue interaction, including puncture, cutting, and friction forces. An estimation algorithm for identifying the parameters of the model is presented. This online approach, which is based on sequential extended Kalman filtering, enables us to characterize the total contact force using an efficient mathematical model. The algorithm compares the axial force measured at the needle base with its expected value and then adapts the model parameters to represent the actual interaction force. While the nature of this problem is very complex, the use of multiple Kalman filters makes the system highly adaptable for capturing the force evolution during an interventional procedure in standard operating conditions. To evaluate the performance of our model, experiments were performed on artificial phantoms.