Magnetic Needle Steering Model Identification Using ExpectationMaximization Deep Brain Stimulation is used to treat Parkinsonxe2x80x99s disease and other neurological disorders by implanting an electrode into the brain via a straightpath needle insertion. Enabling course correction and curved trajectories by using a steerable needle has the potential to improve operative outcomes. In this work, a physically motivated dynamic model for an actively steered magnetictipped needle is derived. Process and measurement noise covariances and model parameter curvature gain are identified using an expectationmaximization (EM) algorithm. Parameter convergence and accuracy are evaluated, and an RMS position trajectory accuracy of 0. 8lmm is calculated for expected conditions. The EM algorithm converged for expected parameter variations in simulation, which supports the EM implementationxe2x80x99s use in identifying the parameters of the model in a physical system.

HumanRobot Visual Interface for 3D Steering of a Flexible, Bioinspired Needle for Neurosurgery Robotic minimally invasive surgery has been a subject of intense research and development over the last three decades, due to the clinical advantages it holds for patients and doctors alike. Particularly for drug delivery mechanisms, higher precision and the ability to follow complex trajectories in three dimensions (3D), has led to interest in flexible, steerable needles such as the programmable beveltip needle (PBN). Steering in 3D, however, holds practical challenges for surgeons, as interfaces are traditionally designed for straight line paths. This work presents a pilot study undertaken to evaluate a novel humanmachine visual interface for the steering of a robotic PBN, where both qualitative evaluation of the interface and quantitative evaluation of the performance of the subjects in following a 3D path are measured. A series of needle insertions are performed in phantom tissue (gelatin) by the experiment subjects. User could adequately use the system with little training and low workload, and reach the target point at the end of the path with millimeter range accuracy.