Prediction of Insertion Force of Bioinspired Needles using Machine Learning Algorithm

Abstract

Simulation of surgical procedures provides a safe and potentially effective method for surgical training and robot-assisted surgery for pre- and intra-operative planning. Accurate modeling of the mechanical behavior of the interface of surgical needles and organs has been well recognized as a major challenge in the development of reliable surgical simulators. Prediction of needle insertion forces especially has been recognized as a major challenge during needle-tissue interactions. In this study, a machine-learning algorithm is proposed to estimate the insertion forces of bioinspired needles.