Using robotics to move a neurosurgeon's hands to the tip of their endoscope.

A major advantage of surgical robots is that they can reduce the invasiveness of a procedure by enabling the clinician to manipulate tools as they would in open surgery but through small incisions in the body. Neurosurgery has yet to benefit from this advantage. Although clinical robots are available for the least invasive neurosurgical procedures, such as guiding electrode insertion, the most invasive brain surgeries, such as tumor resection, are still performed as open manual procedures. To investigate whether robotics could reduce the invasiveness of major brain surgeries while still providing the manipulation capabilities of open surgery, we created a two-armed joystick-controlled endoscopic robot. To evaluate the efficacy of this robot, we developed a set of neurosurgical skill tasks patterned after the steps of brain tumor resection. We also created a patient-derived brain model for pineal tumors, which are located in the center of the brain and are normally removed by open surgery. In comparison, testing with existing manual endoscopic instrumentation, we found that the robot provided access to a much larger working volume at the trocar tip and enabled bimanual tasks without compression of brain tissue adjacent to the trocar. Furthermore, many tasks could be completed faster with the robot. These results suggest that robotics has the potential to substantially reduce the invasiveness of brain surgery by enabling certain procedures currently performed as open surgery to be converted to endoscopic interventions.

Model-based Design of the COAST Guidewire Robot for Large Deflection.

Minimally invasive endovascular procedures involve the manual placement of a guidewire, which is made difficult by vascular tortuosity and the lack of precise tip control. Steerable guidewire systems have been developed with tendon-driven, magnetic, and concentric tube actuation strategies to enable precise tip control, however, selecting machining parameters for such robots does not have a strict procedure. In this paper, we develop a systematic design procedure for selecting the tube pairs of the COaxially Aligned STeerable (COAST) guidewire robot. This includes the introduction of a mechanical model that accounts for micromachining-induced pre-curvatures with the goal of determining design parameters that reduce combined distal tip pre-curvature and minimize abrupt changes in actuated tip position for the COAST guidewire robot through selection of the best flexural rigidity between the tube pairs. We present adjustments in the kinematics modeling of COAST robot tip bending motion, and use these to characterize the bending behavior of the COAST robot for varying geometries of the micromachined tubes, with an average RMSE value for the tip position error of 0.816 mm in the validation study.

Modeling Tendon-actuated Concentric Tube Robots.

Mechanics-based models have been developed to describe the shape of tendon-actuated continuum robots. Models have also been developed to describe the shape of concentric tube robots, i.e., nested combinations of precurved superelastic tubes. While an important class of continuum robots used in endoscopic and intracardiac medical applications combines these two designs, existing models do not cover this combination. Tendon-actuated models are limited to a single tube while concentric tube models do not include tendon-produced forces and moments. This paper derives a mechanics-based model for this hybrid design and assesses it using numerical and physical experiments involving a pair of tendon-actuated tubes. It is demonstrated that, similar to concentric tube robots, relative twisting between the tendon-actuated tubes is an important factor in determining overall robot shape.

Hybrid Tendon and Ball Chain Continuum Robots for Enhanced Dexterity in Medical Interventions.

A hybrid continuum robot design is introduced that combines a proximal tendon-actuated section with a distal telescoping section comprised of permanent-magnet spheres actuated using an external magnet. While, individually, each section can approach a point in its workspace from one or at most several orientations, the two-section combination possesses a dexterous workspace. The paper describes kinematic modeling of the hybrid design and provides a description of the dexterous workspace. We present experimental validation which shows that a simplified kinematic model produces tip position mean and maximum errors of 3% and 7% of total robot length, respectively.

Kinematic Modeling and Jacobian-based Control of the COAST Guidewire Robot.

Manual guidewire navigation and placement for minimally invasive surgeries suffer from technical challenges due to imprecise tip motion control to traverse highly tortuous vasculature. Robotically steerable guidewires can address these challenges by actuating a compliant tip through multiple degrees-of-freedom for maneuvering through vascular pathways. In this paper, we detail the kinematic mapping of a COaxially Aligned STeerable (COAST) guidewire robot that is capable of executing follow-the-leader motion in three dimensional vascular pathways. We also develop an analytical Jacobian model to perform velocity kinematics for the robot and finally, we implement Jacobian-based control to demonstrate follow-the-leader motion of the guidewire in free space, within 3D-printed phantoms, and within ex vivo animal vasculature.

Towards FBG-Based Shape Sensing for Micro-scale and Meso-Scale Continuum Robots with Large Deflection.

Endovascular and endoscopic surgical procedures require micro-scale and meso-scale continuum robotic tools to navigate complex anatomical structures. In numerous studies, fiber Bragg grating (FBG) based shape sensing has been used for measuring the deflection of continuum robots on larger scales, but has proved to be a challenge for micro-scale and meso-scale robots with large deflections. In this paper, we have developed a sensor by mounting an FBG fiber within a micromachined nitinol tube whose neutral axis is shifted to one side due to the machining. This shifting of the neutral axis allows the FBG core to experience compressive strain when the tube bends. The fabrication method of the sensor has been explicitly detailed and the sensor has been tested with two tendon-driven micro-scale and meso-scale continuum robots with outer diameters of 0.41 mm and 1.93 mm respectively. The compact sensor allows repeatable and reliable estimates of the shape of both scales of robots with minimal hysteresis. We propose an analytical model to derive the curvature of the robot joints from FBG fiber strain and a static model that relates joint curvature to the tendon force. Finally, as proof-of-concept, we demonstrate the feasibility of our sensor assembly by combining tendon force feedback and the FBG strain feedback to generate reliable estimates of joint angles for the meso-scale robot.

A system for bedside assistance that integrates a robotic bed and a mobile manipulator.

Various situations, such as injuries or long-term disabilities, can result in people receiving physical assistance while in bed. We present a robotic system for bedside assistance that consists of a robotic bed and a mobile manipulator (i.e., a wheeled robot with arms) that work together to provide better assistance. Many assistive tasks depend on moving with respect to the person's body, and the complementary physical and perceptual capabilities of the two robots help with respect to this general goal. The system provides autonomy for common tasks, as well as an interface for direct teleoperation of the two robots. Autonomy handles coarse motions of the robots by estimating the person's pose using a pressure sensing mat and then moving the robots to configurations optimized for the task. After completing these motions, the user is given fine control of the robots to complete the task. In an evaluation using a medical mannequin, we found that the robotic bed's motion and perception each improved the assistive robotic system's performance. The system achieved 100% success over 9 trials involving 3 tasks. Using the system with the bed movement or the body pose estimation capabilities turned off resulted in success in only 33% or 78% of the trials, respectively. We also evaluated our system with Henry Evans, a person with severe quadriplegia, in his home. In a formal test, Henry successfully used the bedside-assistance system to perform 3 different tasks, 5 times each, without any failures. Henry's feedback on the system was positive regarding usefulness and ease of use, and he noted benefits of using our system over fully manual teleoperation. Overall, our results suggest that a robotic bed and a mobile manipulator can work collaboratively to provide effective personal assistance and that the combination of the two robots is beneficial.