Allison M. Okamura

Force modeling for needle insertion into soft tissue

The modeling of forces during needle insertion into soft tissue is important for accurate surgical simulation, preoperative planning, and intelligent robotic assistance for percutaneous therapies. We present a force model for needle insertion and experimental procedures for acquiring data from ex vivo tissue to populate that model. Data were collected from bovine livers using a one-degree-of-freedom robot equipped with a load cell and needle attachment. computed tomography imaging was used to segment the needle insertion process into phases identifying different relative velocities between the needle and tissue. The data were measured and modeled in three parts: 1) capsule stiffness, a nonlinear spring model; 2) friction, a modified Karnopp model; and 3) cutting, a constant for a given tissue. In addition, we characterized the effects of needle diameter and tip type on insertion force using a silicone rubber phantom. In comparison to triangular and diamond tips, a bevel tip causes more needle bending and is more easily affected by tissue density variations. Forces for larger diameter needles are higher due to increased cutting and friction forces.

Nonholonomic Modeling of Needle Steering

As a flexible needle with a bevel tip is pushed through soft tissue, the asymmetry of the tip causes the needle to bend. We propose that, by using nonholonomic kinematics, control, and path planning, an appropriately designed needle can be steered through tissue to reach a specified 3D target. Such steering capability could enhance targeting accuracy and may improve outcomes for percutaneous therapies, facilitate research on therapy effectiveness, and eventually enable new minimally invasive techniques. In this paper, we consider a first step toward active needle steering: design and experimental validation of a nonholonomic model for steering flexible needles with bevel tips. The model generalizes the standard three degree-of-freedom (DOF) nonholonomic unicycle and bicycle models to 6 DOF using Lie group theory. Model parameters are fit using experimental data, acquired via a robotic device designed for the specific purpose of inserting and steering a flexible needle. The experiments quantitatively validate the bevel-tip needle steering model, enabling future research in flexible needle path planning, control, and simulation.

A velocity-dependent model for needle insertion in soft tissue

Models that predict the soft tissue deformation caused by needle insertion could improve the accuracy of procedures such as brachytherapy and needle biopsy. Prior work on needle insertion modeling has focused on static deformation; the experiments presented here show that dynamic effects such as relaxation are important. An experimental setup is described for recording and measuring the deformation that occurs with needle insertion into a soft tissue phantom. Analysis of the collected data demonstrates the time- and velocity-dependent nature of the deformation. Deformation during insertion is shown to be well represented using a velocity-dependent force function with a linear elastic finite element model. The models accuracy is limited to the period during needle motion, indicating that a viscoelastic tissue model may be required to capture tissue relaxation after the needle stops.

An overview of dexterous manipulation

Presents an overview of research in dexterous manipulation. We first define robotic dexterous manipulation in comparison to traditional robotics and human manipulation. Next, kinematics, contact types and forces are used to formulate the dexterous manipulation problem. Dexterous motion planning is described, which includes grasp planning and quality measures. We look at mid- and low-level control frameworks, and then compare manipulation versus exploration. Finally, we list accomplishments in the different areas of dexterous manipulation research, and highlight important areas for future work.

Haptic feedback in robot-assisted minimally invasive surgery

Purpose of review Robot-assisted minimally invasive surgery (RMIS) holds great promise for improving the accuracy and dexterity of a surgeon and minimizing trauma to the patient. However, widespread clinical success with RMIS has been marginal. It is hypothesized that the lack of haptic (force and tactile) feedback presented to the surgeon is a limiting factor. This review explains the technical challenges of creating haptic feedback for robot-assisted surgery and provides recent results that evaluate the effectiveness of haptic feedback in mock surgical tasks. Recent findings Haptic feedback systems for RMIS are still under development and evaluation. Most provide only force feedback, with limited fidelity. The major challenge at this time is sensing forces applied to the patient. A few tactile feedback systems for RMIS have been created, but their practicality for clinical implementation needs to be shown. It is particularly difficult to sense and display spatially distributed tactile information. The cost–benefit ratio for haptic feedback in RMIS has not been established. Summary The designs of existing commercial RMIS systems are not conducive for force feedback, and creative solutions are needed to create compelling tactile feedback systems. Surgeons, engineers, and neuroscientists should work together to develop effective solutions for haptic feedback in RMIS.

Vision-assisted control for manipulation using virtual fixtures

We present the design and implementation of a vision-based system for cooperative manipulation at millimeter to micrometer scales. The system is based on an admittance control algorithm that implements a broad class of guidance modes called virtual fixtures. A virtual fixture, like a real fixture, limits the motion of a tool to a prescribed class or range of motions. We describe how both hard (unyielding) and soft (yielding) virtual fixtures can be implemented in this control framework. We then detail the construction of virtual fixtures for point positioning and curve following as well as extensions of these to tubes, cones, and sequences thereof. We also describe an implemented system using the JHU Steady Hand Robot. The system uses computer vision as a sensor for providing a reference trajectory, and the virtual fixture control algorithm then provides haptic feedback to implemented direct, shared manipulation. We provide extensive experimental results detailing both system performance and the effects of virtual fixtures on human speed and accuracy.

Planning for Steerable Bevel-tip Needle Insertion Through 2D Soft Tissue with Obstacles

We explore motion planning for a new class of highly flexible bevel-tip medical needles that can be steered to previously unreachable targets in soft tissue. Planning for these procedures is difficult because the needles bend during insertion and cause the surrounding soft tissues to displace and deform. In this paper, we develop a planning algorithm for insertion of highly flexible bevel-tip needles into soft tissues with obstacles in a 2D imaging plane. Given an initial needle insertion plan specifying location, orientation, bevel rotation, and insertion distance, the planner combines soft tissue modeling and numerical optimization to generate a needle insertion plan that compensates for simulated tissue de formations, locally avoids polygonal obstacles, and minimizes needle insertion distance. The simulator computes soft tissue deformations using a finite element model that incorporates the effects of needle tip and frictional forces using a 2D mesh. We formulate the planning problem as a constrained nonlinear optimization problem that is locally minimized using a penalty method that converts the formulation to a sequence of unconstrained optimization problems. We apply the planner to bevel-right and bevel-left needles and generate plans for targets that are unreachable by rigid needles.

Haptic Virtual Fixtures for Robot-Assisted Manipulation

Haptic virtual fixtures are software-generated force and position signals applied to human operators in order to improve the safety, accuracy, and speed of robot-assisted manipulation tasks. Virtual fixtures are effective and intuitive because they capitalize on both the accuracy of robotic systems and the intelligence of human operators. In this paper, we discuss the design, analysis, and implementation of two categories of virtual fixtures: guidance virtual fixtures, which assist the user in moving the manipulator along desired paths or surfaces in the workspace, and forbidden-region virtual fixtures, which prevent the manipulator from entering into forbidden regions of the workspace. Virtual fixtures are analyzed in the context of both cooperative manipulation and telemanipulation systems, considering issues related to stability, passivity, human modeling, and applications.

Mechanics of Flexible Needles Robotically Steered through Soft Tissue

The tip asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. This enables robotic needle steering, which can be used in medical procedures to reach subsurface targets inaccessible by straight-line trajectories. However, accurate path planning and control of needle steering require models of needle-tissue interaction. Previous kinematic models required empirical observations of each needle and tissue combination in order to fit model parameters. This study describes a mechanics-based model of robotic needle steering, which can be used to predict needle behavior and optimize system design based on fundamental mechanical and geometrical properties of the needle and tissue. We first present an analytical model for the loads developed at the tip, based on the geometry of the bevel edge and material properties of soft-tissue simulants (gels). We then present a mechanics-based model that calculates the deflection of a bevel-tipped needle inserted through a soft elastic medium. The model design is guided by microscopic observations of needle-gel interactions. The energy-based formulation incorporates tissue-specific parameters, and the geometry and material properties of the needle. Simulation results follow similar trends (deflection and radius of curvature) to those observed in experimental studies of robotic needle insertion.

Design Considerations for Robotic Needle Steering

Many medical procedures involve the use of needles, but targeting accuracy can be limited due to obstacles in the needle’s path, shifts in target position caused by tissue deformation, and undesired bending of the needle after insertion. In order to address these limitations, we have developed robotic systems that actively steer a needle in soft tissue. A bevel (asymmetric) tip causes the needle to bend during insertion, and steering is enhanced when the needle is very flexible. An experimental needle steering robot was designed that includes force/torque sensing, horizontal needle insertion, stereo image data acquisition, and controlled actuation of needle rotation and translation. Experiments were performed with a phantom tissue to determine the effects of insertion velocity and bevel tip angle on the needle path, as well as the forces acting on the needle during insertion. Results indicate that needle steering inside tissue does not depend on insertion velocity, but does depend on bevel tip angle. In addition, the forces acting on the needle are directly related to the insertion velocity.