Estimation of needle tissue interaction based on non-linear elastic modulus and friction force patterns

Incidence of cancer is growing worldwide according to statistics, what increments costs of national health systems and decreases quality of life of cancer patients. Percutaneous cancer treatments can reduce the physical burden of cancer patients due to its minimally invasiveness and allow to treat small size tumors. Robotic needle placement has been proposed to overcome the difficulties of manual needle placement, which has not enough accuracy. Until now, researchers have focused on developing deterministic models for pre or intra-operative control. In this paper, we propose a novel approach by extracting patterns in needle insertion force that can provide information about the current status of needle tissue interaction. In particular, we focus in estimating the non-linear local elastic modulus and friction status in real-time during needle insertion.