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.

Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing

In the last decade, various robotic platforms have been introduced that could support delicate retinal surgeries. Concurrently, to provide semantic understanding of the surgical area, recent advances have enabled microscope-integrated intraoperative Optical Coherent Tomography (iOCT) with high-resolution 3D imaging at near video rate. The combination of robotics and semantic understanding enables task autonomy in robotic retinal surgery, such as for subretinal injection. This procedure requires precise needle insertion for best treatment outcomes. However, merging robotic systems with iOCT introduces new challenges. These include, but are not limited to high demands on data processing rates and dynamic registration of these systems during the procedure. In this work, we propose a framework for autonomous robotic navigation for subretinal injection, based on intelligent real-time processing of iOCT volumes. Our method consists of an instrument pose estimation method, an online registration between the robotic and the iOCT system, and trajectory planning tailored for navigation to an injection target. We also introduce intelligent virtual B-scans, a volume slicing approach for rapid instrument pose estimation, which is enabled by Convolutional Neural Networks (CNNs). Our experiments on ex-vivo porcine eyes demonstrate the precision and repeatability of the method. Finally, we discuss identified challenges in this work and suggest potential solutions to further the development of such systems.

Real-time Pose Tracking for a Continuum Guidewire Robot under Fluoroscopic Imaging

Atherosclerosis is a medical condition that causes buildup of plaque in the blood vessels and narrowing of the arteries. Surgeons often treat this condition through angioplasty with catheter placements. Continuum guidewire robots offer significant advantages for catheter placements due to their dexterity. Tracking these guidewire robots and their surrounding workspace under fluoroscopy in real-time can be useful for visualization and accurate control. This paper discusses algorithms and methods to track the shape and orientation of the guidewire and the surrounding workspaces of phantom vasculatures in real-time under C-arm fluoroscopy. The shape of continuum guidewires is found through a semantic segmentation architecture based on MobileNetv2 with a Tversky loss function to deal with class imbalances. This shape is refined through medial axis filtering and parametric curve fitting to quantitatively describe the guidewire's pose. Using a constant curvature assumption for the guidewire's bending segments, the parameters that describe the joint variables are estimated in real-time for a tendon-actuated COaxially Aligned STeerable (COAST) guidewire robot and tracked through its traversal of an aortic bifurcation phantom. The accuracy of the tracking is ~90% and the execution times are within 100ms, and hence this method is deemed suitable for real-time tracking.

Magnetic Ball Chain Robots for Endoluminal Interventions

This paper introduces a novel class of hyperredundant robots comprised of chains of permanently magnetized spheres enclosed in a cylindrical polymer skin. With their shape controlled using an externally-applied magnetic field, the spherical joints of these robots enable them to bend to very small radii of curvature. These robots can be used as steerable tips for endoluminal instruments. A kinematic model is derived based on minimizing magnetic and elastic potential energy. Simulation is used to demonstrate the enhanced steerability of these robots in comparison to magnetic soft continuum robots designed using either distributed or lumped magnetic material. Experiments are included to validate the model and to demonstrate the steering capability of ball chain robots in bifurcating channels.

Flexible Needle Bending Model for Spinal Injection Procedures

An in situ needle manipulation technique used by physicians when performing spinal injections is modeled to study its effect on needle shape and needle tip position. A mechanics-based model is proposed and solved using finite element method. A test setup is presented to mimic the needle manipulation motion. Tissue phantoms made from plastisol as well as porcine skeletal muscle samples are used to evaluate the model accuracy against medical images. The effect of different compression models as well as model parameters on model accuracy is studied, and the effect of needle-tissue interaction on the needle remote center of motion is examined. With the correct combination of compression model and model parameters, the model simulation is able to predict needle tip position within submillimeter accuracy.

Fluoroscopic Image-Based 3-D Environment Reconstruction and Automated Path Planning for a Robotically Steerable Guidewire

Cardiovascular diseases are the leading cause of death globally and surgical treatments for these often begin with the manual placement of a long compliant wire, called a guidewire, through different vasculature. To improve procedure outcomes and reduce radiation exposure, we propose steps towards a fully automated approach for steerable guidewire navigation within vessels. In this paper, we utilize fluoroscopic images to fully reconstruct 3-D printed phantom vasculature models by using a shape-from-silhouette algorithm. The reconstruction is subsequently de-noised using a deep learning-based encoder-decoder network and morphological filtering. This volume is used to model the environment for guidewire traversal. Following this, we present a novel method to plan an optimal path for guidewire traversal in three-dimensional vascular models through the use of slice planes and a modified hybrid A-star algorithm. Finally, the developed reconstruction and planning approaches are applied to an ex vivo porcine aorta, and navigation is demonstrated through the use of a tendon-actuated COaxially Aligned STeerable guidewire (COAST).

Influence of Antagonistic Tensions on Distributed Friction Forces of Multisegment Tendon-Driven Continuum Manipulators With Irregular Geometry

In this paper, we thoroughly analyze the effect of single-tendon and antagonistic tendons actuation on tension loss of multi-segment tendon-driven continuum manipulators (TD-CMs) with irregular geometry. To this end, we propose a generic analytical modeling approach and iterative algorithm that can solve the unknown correlation between distributed friction force, tendons' tension transmission loss, and planar deformation behavior of TD-CMs during tendons' pulling and releasing phases. The proposed generic model solely relies on known input tendons' tensions and does not require a priori knowledge of the manipulator's shape and/or other experimental conditions. To investigate the influence of actuation type on tension loss and deformation behavior of TD-CMs, we fabricated two different TD-CMs and performed various simulation and experimental studies with single-tendon and antagonistic tensions actuations. The obtained results indicate the importance of considering the effect of distributed friction force and actuation type on tension(s) loss of multi-segment TD-CMs. Moreover, it clearly demonstrates the efficacy and accuracy of the proposed model in providing insights and understanding of tension transmission process in various types of actuations in multi-segment TD-CMs with irregular geometry.

A-SEE: Active-Sensing End-effector Enabled Probe Self-Normal-Positioning for Robotic Ultrasound Imaging Applications

Conventional manual ultrasound (US) imaging is a physically demanding procedure for sonographers. A robotic US system (RUSS) has the potential to overcome this limitation by automating and standardizing the imaging procedure. It also extends ultrasound accessibility in resource-limited environments with the shortage of human operators by enabling remote diagnosis. During imaging, keeping the US probe normal to the skin surface largely benefits the US image quality. However, an autonomous, real-time, low-cost method to align the probe towards the direction orthogonal to the skin surface without pre-operative information is absent in RUSS. We propose a novel end-effector design to achieve self-normal-positioning of the US probe. The end-effector embeds four laser distance sensors to estimate the desired rotation towards the normal direction. We then integrate the proposed end-effector with a RUSS system which allows the probe to be automatically and dynamically kept to normal direction during US imaging. We evaluated the normal positioning accuracy and the US image quality using a flat surface phantom, an upper torso mannequin, and a lung ultrasound phantom. Results show that the normal positioning accuracy is 4.17 ± 2.24 degrees on the flat surface and 14.67 ± 8.46 degrees on the mannequin. The quality of the RUSS collected US images from the lung ultrasound phantom was equivalent to that of the manually collected ones.

Multiphysical Analytical Modeling and Design of A Magnetically Steerable Robotic Catheter for Treatment of Peripheral Artery Disease

This article presents a unique multiphysical analytical modeling framework and solution algorithm to provide an effective tool for design of magnetically steerable robotic catheters (MSRCs) experiencing external interaction loads. Particularly, in this study, we are interested in design and fabrication of a MSRC with flexural patterns for treatment of peripheral artery disease (PAD). Aside from the parameters involved in the magnetic actuation system and the external interaction loads acting on the MSRC, the considered flexural patterns have a critical role on the deformation behavior and steerability of the proposed MSRC. Therefore, to optimally design such MSRC, we utilized the proposed multiphysical modeling approach and thoroughly evaluated the influence of involved parameters on the performance of the MSRC via two simulations studies. We also conducted experimental studies in a free bending condition and in the presence of different external interaction loads on two custom-designed MSRCs to thoroughly evaluate the efficacy of the proposed multiphysical model and solution algorithm. Our analysis demonstrates the accuracy of the proposed approach and necessity of utilizing such models to optimally design a MSRC before fabrication procedure.

ColibriDoc: An Eye-in-Hand Autonomous Trocar Docking System

Retinal surgery is a complex medical procedure that requires exceptional expertise and dexterity. For this purpose, several robotic platforms are currently under development to enable or improve the outcome of microsurgical tasks. Since the control of such robots is often designed for navigation inside the eye in proximity to the retina, successful trocar docking and insertion of the instrument into the eye represents an additional cognitive effort, and is therefore one of the open challenges in robotic retinal surgery. For this purpose, we present a platform for autonomous trocar docking that combines computer vision and a robotic setup. Inspired by the Cuban Colibri (hummingbird) aligning its beak to a flower using only vision, we mount a camera onto the endeffector of a robotic system. By estimating the position and pose of the trocar, the robot is able to autonomously align and navigate the instrument towards the Trocar Entry Point (TEP) and finally perform the insertion. Our experiments show that the proposed method is able to accurately estimate the position and pose of the trocar and achieve repeatable autonomous docking. The aim of this work is to reduce the complexity of the robotic setup prior to the surgical task and therefore, increase the intuitiveness of the system integration into clinical workflow.

Spotlight-based 3D Instrument Guidance for Autonomous Task in Robot-assisted Retinal Surgery

Retinal surgery is known to be a complicated and challenging task for an ophthalmologist even for retina specialists. Image guided robot-assisted intervention is among the novel and promising solutions that may enhance human capabilities during microsurgery. In this paper, a novel method is proposed for 3D navigation of a microsurgical instrument based on the projection of a spotlight during robot-assisted retinal surgery. To test the feasibility and effectiveness of the proposed method, a vessel tracking task in a phantom with a Remote Center of Motion (RCM) constraint is performed by the Steady-Hand Eye Robot (SHER). The results are compared to manual tracking, cooperative control tracking with the SHER and spotlight-based automatic tracking with SHER. The reported results are that the spotlight-based automatic tracking with SHER can reach an average tracking error of 0.013 mm and keeping distance error of 0.1 mm from the desired range demonstrating a significant improvement compared to manual or cooperative control methods alone.

Automated Implant Resizing for Single-Stage Cranioplasty

Patient-specific customized cranial implants (CCIs) are designed to fill the bony voids in the cranial and craniofacial skeleton. The current clinical approach during single-stage cranioplasty involves a surgeon modifying an oversized CCI to fit a patient's skull defect. The manual process, however, can be imprecise and time-consuming. This paper presents an automated surgical workflow with a robotic workstation for intraoperative CCI modification that provides higher resizing accuracy compared to the manual approach. We proposed a 2-scan method for intraoperative patient-to-CT registration using reattachable fiducial markers to address the registration issue caused by the clinical draping requirement. First, the draped defected skull was 3D scanned and registered to the CT space using our proposed 2-scan registration method. Next, our algorithm generates a robot cutting toolpath based on the 3D defect model. The robot then performs automatic 3D scanning to localize the implant and resizes the implant to match the cranial defect. We evaluated the implant resizing accuracy of the proposed paradigm against the resizing accuracy of the manual approach by an expert surgeon on two plastic skulls and two cadavers. The evaluation results showed that our system was able to decrease the bone gap distance by more than 60% and 30% on plastic skulls and cadavers respectively compared to the manual approach, indicating lower risk of post-surgical complication and better aesthetic restoration.

Semi-Automated Extraction of Lens Fragments via a Surgical Robot Using Semantic Segmentation of OCT Images with Deep Learning - Experimental Results in ex vivo Animal Model

The overarching goal of this work is to demonstrate the feasibility of using optical coherence tomography (OCT) to guide a robotic system to extract lens fragments from ex vivo pig eyes. A convolutional neural network (CNN) was developed to semantically segment four intraocular structures (lens material, capsule, cornea, and iris) from OCT images. The neural network was trained on images from ten pig eyes, validated on images from eight different eyes, and tested on images from another ten eyes. This segmentation algorithm was incorporated into the Intraocular Robotic Interventional Surgical System (IRISS) to realize semi-automated detection and extraction of lens material. To demonstrate the system, the semi-automated detection and extraction task was performed on seven separate ex vivo pig eyes. The developed neural network exhibited 78.20% for the validation set and 83.89% for the test set in mean intersection over union metrics. Successful implementation and efficacy of the developed method were confirmed by comparing the preoperative and postoperative OCT volume scans from the seven experiments.

A Soft Robotic Sleeve for Safer Colonoscopy Procedures

Colonoscopy is the gold standard for colorectal cancer diagnosis; however, limited instrument dexterity and no sensor feedback can hamper procedure safety and acceptance. We propose a soft robotic sleeve to provide sensor feedback and additional actuation capabilities to improve safety during navigation in colonoscopy. The robot can be mounted around current endoscopic instrumentation as a disposable "add-on", avoiding the need for dedicated or customized instruments and without disrupting current surgical workflow. We focus on design, finite element analysis, fabrication, and experimental characterization and validation of the soft robotic sleeve. The device integrates soft optical sensors to monitor contact interaction forces between the colon and the colonoscope and soft robotic actuators that can be automatically deployed if excessive force is detected, to guarantee pressure redistribution on a larger contact area of the colon. The system can be operated by a surgeon via a graphic user interface that displays contact force values and enables independent or coordinated pressurization of the soft actuators upon demand, in case deemed necessary to aid navigation or distend colon tissue.

An Active Steering Hand-held Robotic System for Minimally Invasive Orthopaedic Surgery Using a Continuum Manipulator

This paper presents the development and experimental evaluation of an active steering hand-held robotic system for milling and curved drilling in minimally invasive orthopaedic interventions. The system comprises a cable-driven continuum dexterous manipulator (CDM), an actuation unit with a handpiece, and a flexible, rotary cutting tool. Compared to conventional rigid drills, the proposed system enhances dexterity and reach in confined spaces in surgery, while providing direct control to the surgeon with sufficient stability while cutting/milling hard tissue. Of note, for cases that require precise motion, the system is able to be mounted on a positioning robot for additional controllability. A proportional-derivative (PD) controller for regulating drive cable tension is proposed for the stable steering of the CDM during cutting operations. The robotic system is characterized and tested with various tool rotational speeds and cable tensions, demonstrating successful cutting of three-dimensional and curvilinear tool paths in simulated cancellous bone and bone phantom. Material removal rates (MRRs) of up to 571 mm3/s are achieved for stable cutting, demonstrating great improvement over previous related works.

Camera-Robot Calibration for the da Vinci® Robotic Surgery System

The development of autonomous or semi-autonomous surgical robots stands to improve the performance of existing teleoperated equipment, but requires fine hand-eye calibration between the free-moving endoscopic camera and patient-side manipulator arms (PSMs). A novel method of solving this problem for the da Vinci® robotic surgical system and kinematically similar systems is presented. First, a series of image-processing and optical-tracking operations are performed to compute the coordinate transformation between the endoscopic camera view frame and an optical-tracking marker permanently affixed to the camera body. Then, the kinematic properties of the PSM are exploited to compute the coordinate transformation between the kinematic base frame of the PSM and an optical marker permanently affixed thereto. Using these transformations, it is then possible to compute the spatial relationship between the PSM and the endoscopic camera using only one tracker snapshot of the two markers. The effectiveness of this calibration is demonstrated by successfully guiding the PSM end effector to points of interest identified through the camera. Additional tests on a surgical task, namely grasping a surgical needle, are also performed to validate the proposed method. The resulting visually-guided robot positioning accuracy is better than the earlier hand-eye calibration results reported in the literature for the da Vinci® system, while supporting intraoperative update of the calibration and requiring only devices that are already commonly used in the surgical environment.

Optical Coherence Tomography-Guided Robotic Ophthalmic Microsurgery via Reinforcement Learning from Demonstration

Ophthalmic microsurgery is technically difficult because the scale of required surgical tool manipulations challenge the limits of the surgeon's visual acuity, sensory perception, and physical dexterity. Intraoperative optical coherence tomography (OCT) imaging with micrometer-scale resolution is increasingly being used to monitor and provide enhanced real-time visualization of ophthalmic surgical maneuvers, but surgeons still face physical limitations when manipulating instruments inside the eye. Autonomously controlled robots are one avenue for overcoming these physical limitations. We demonstrate the feasibility of using learning from demonstration and reinforcement learning with an industrial robot to perform OCT-guided corneal needle insertions in an ex vivo model of deep anterior lamellar keratoplasty (DALK) surgery. Our reinforcement learning agent trained on ex vivo human corneas, then outperformed surgical fellows in reaching a target needle insertion depth in mock corneal surgery trials. This work shows the combination of learning from demonstration and reinforcement learning is a viable option for performing OCT guided robotic ophthalmic surgery.

Online Disturbance Estimation for Improving Kinematic Accuracy in Continuum Manipulators

Continuum manipulators are flexible robots which undergo continuous deformation as they are actuated. To describe the elastic deformation of such robots, kinematic models have been developed and successfully applied to a large variety of designs and to various levels of constitutive stiffness. Independent of the design, kinematic models need to be calibrated to best describe the deformation of the manipulator. However, even after calibration, unmodeled effects such as friction, nonlinear elastic and/or spatially varying material properties as well as manufacturing imprecision reduce the accuracy of these models. In this paper, we present a method for improving the accuracy of kinematic models of continuum manipulators through the incorporation of orientation sensor feedback. We achieve this through the use of a "disturbance wrench", which is used to compensate for these unmodeled effects, and is continuously estimated based on orientation sensor feedback as the robot moves through its workspace. The presented method is applied to the HydroJet, a waterjet-actuated soft continuum manipulator, and shows an average of 40% reduction in root mean square position and orientation error in the two most common types of kinematic models for continuum manipulators, a Cosserat rod model and a pseudo-rigid body model.

Magnetically Steered Robotic Insertion of Cochlear-Implant Electrode Arrays: System Integration and First-In-Cadaver Results

Cochlear-implant electrode arrays (EAs) must be inserted accurately and precisely to avoid damaging the delicate anatomical structures of the inner ear. It has previously been shown on the benchtop that using magnetic fields to steer magnet-tipped EAs during insertion reduces insertion forces, which correlate with insertion errors and damage to internal cochlear structures. This paper presents several advancements toward the goal of deploying magnetic steering of cochlear-implant EAs in the operating room. In particular, we integrate image guidance with patient-specific insertion vectors, we incorporate a new nonmagnetic insertion tool, and we use an electromagnetic source, which provides programmable control over the generated field. The electromagnet is safer than prior permanent-magnet approaches in two ways: it eliminates motion of the field source relative to the patient's head and creates a field-free source in the power-off state. Using this system, we demonstrate system feasibility by magnetically steering EAs into a cadaver cochlea for the first time. We show that magnetic steering decreases average insertion forces, in comparison to manual insertions and to image-guided robotic insertions alone.

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.

Supervised Autonomous Electrosurgery via Biocompatible Near-Infrared Tissue Tracking Techniques

Autonomous robotic surgery systems aim to improve patient outcomes by leveraging the repeatability and consistency of automation and also reducing human induced errors. However, intraoperative autonomous soft tissue tracking and robot control still remains a challenge due to the lack of structure, and high deformability of such tissues. In this paper, we take advantage of biocompatible Near-Infrared (NIR) marking methods and develop a supervised autonomous 3D path planning, filtering, and control strategy for our Smart Tissue Autonomous Robot (STAR) to enable precise and consistent incisions on complex 3D soft tissues. Our experimental results on cadaver porcine tongue samples indicate that the proposed strategy reduces surface incision error and depth incision error by 40.03% and 51.5%, respectively, compared to a teleoperation strategy via da Vinci. Furthermore, compared to an autonomous path planning method with linear interpolation between the NIR markers, the proposed strategy reduces the incision depth error by 48.58% by taking advantage of 3D tissue surface information.

Sensorless Estimation of the Planar Distal Shape of a Tip-Actuated Endoscope

Traditional endoscopes consist of a flexible body and a steerable tip with therapeutic capability. Although prior endoscopes have relied on operator pushing for actuation, recent robotic concepts have relied on the application of a tip force for guidance. In such case, the body of the endoscope can be passive and compliant; however, the body can have significant effect on mechanics of motion and may require modeling. As the endoscope body's shape is often unknown, we have developed an estimation method to recover the approximate distal shape, local to the endoscope's tip, where the tip position and orientation are the only sensed parameters in the system. We leverage a planar dynamic model and extended Kalman filter to obtain a constant-curvature shape estimate of a magnetically guided endoscope. We validated this estimator in both dynamic simulations and on a physical platform. We then used this estimate in a feed-forward control scheme and demonstrated improved trajectory following. This methodology can enable the use of inverse-dynamic control for the tip-based actuation of an endoscope, without the need for shape sensing.

Explicit Model Predictive Control of a Magnetic Flexible Endoscope

In this paper, explicit model predictive control is applied in conjunction with nonlinear optimisation to a magnetically actuated flexible endoscope for the first time. The approach is aimed at computing the motion of the external permanent magnet, given the desired forces and torques. The strategy described here takes advantage of the nonlinear nature of the magnetic actuation and explicitly considers the workspace boundaries, as well as the actuation constraints. Initially, a simplified dynamic model of the tethered capsule, based on the Euler-Lagrange equations is developed. Subsequently, the explicit model predictive control is described and a novel approach for the external magnet positioning, based on a single step, nonlinear optimisation routine, is proposed. Finally, the strategy is implemented on the experimental platform, where bench-top trials are performed on a realistic colon phantom, showing the effectiveness of the technique. The work presented here constitutes an initial exploration for model-based control techniques applied to magnetically manipulated payloads, the techniques described here may be applied to a wide range of devices, including flexible endoscopes and wireless capsules. To our knowledge, this is the first example of advanced closed loop control of magnetic capsules.

Design, Analysis, and Evaluation of a Remotely Actuated MRI-Compatible Neurosurgical Robot

The paper presents an MRI-compatible neurosurgical robotic system that is designed to operate the head-mounted meso-scale 6-degree-of-freedom (DoF) spring-based MINIR-II. The robotic system consists of an actuation module, a transmission module, and the robot module. The transmission module consist of a switching mechanism for reducing the required number of motors by half, an innovative linkage mechanism to insert and retract the robot with minimal tendon displacement and friction loss, and a quick-connect mechanism for easy attachment of the disposable MINIR-II. Design, analysis, and development of each module are described in detail. Most of the critical components such as the robot, the quick-connect, the linkage mechanism, and various gear-pulley combinations in our design are 3-D printed. Preliminary mechanical properties characterization of the system and the capability of the underactuated system to replicate the critical functions of the 6-DoF robot are presented. The robot motion capability in a brain phantom model and its MRI compatibility in a 7-Tesla magnet were verified.

Can Elastic Instability be Beneficial in Concentric Tube Robots?

Concentric tube manipulators exhibit elastic instability in which tubes snap from one configuration to another, rapidly releasing stored strain energy. While this has long been viewed as a negative phenomenon to be avoided at all costs, in this paper we explore for the first time whether the effect can be harnessed beneficially for certain applications. Specifically, we show that the energy released in an instability can be useful for challenging, high-force surgical tasks such as driving a needle through tissue. We use concentric tube models to define the energy released during elastic instability and experimentally evaluate a two-tube concentric manipulator that can drive suture needles through tissue by harnessing elastic instability beneficially.

Through the Eustachian Tube and Beyond: A New Miniature Robotic Endoscope to See Into The Middle Ear

This paper presents a novel miniature robotic endoscope that is small enough to pass through the Eustachian tube and provide visualization of the middle ear (ME). The device features a miniature bending tip previously conceived of as a small-scale robotic wrist that has been adapted to carry and aim a small chip-tip camera and fiber optic light sources. The motivation for trans-Eustachian tube ME inspection is to provide a natural-orifice-based route to the ME that does not require cutting or lifting the eardrum, as is currently required. In this paper, we first perform an analysis of the ME anatomy and use a computational design optimization platform to derive the kinematic requirements for endoscopic inspection of the ME through the Eustachian tube. Based on these requirements, we fabricate the proposed device and use it to demonstrate the feasibility of ME inspection in an anthropomorphic model, i.e. a 3D-printed ME phantom generated from patient image data. We show that our prototype provides > 74% visibility coverage of the sinus tympani, a region of the ME crucial for diagnosis, compared to an average of only 6.9% using a straight, non-articulated endoscope through the Eustachian Tube.

Autonomous Retroflexion of a Magnetic Flexible Endoscope

Retroflexion during colonoscopy is typically only practiced in the wider proximal and distal ends of the large intestine owing to the stiff nature of the colonoscope. This inability to examine the proximal side of the majority of colon folds contributes to today's suboptimal colorectal cancer detection rates. We have developed an algorithm for autonomous retroflexion of a flexible endoscope that is actuated magnetically from the tip. The magnetic wrench applied on the tip of the endoscope is optimized in real-time with data from pose detection to compute motions of the actuating magnet. This is the first example of a completely autonomous maneuver by a magnetic endoscope for exploration of the gastrointestinal tract. The proposed approach was validated in plastic tubes of various diameters with a success rate of 98.8% for separation distances up to 50 mm. Additionally, a set of trials was conducted in an excised porcine colon observing a success rate of 100% with a mean time of 19.7 s. In terms of clinical safety, the maximum stress that is applied on the colon wall with our methodology is an order of magnitude below what would damage tissue.

Comparing a Mechanical Analogue With the Da Vinci User Interface: Suturing at Challenging Angles

The da Vinci Surgical System offers a natural user interface and wrist articulation, which enable suturing and other complex surgical actions in confined spaces. However, both the one-time cost of the system and the recurring cost of the limited-use instruments remain high. This has motivated the development of several hand-held alternatives-some partially motorized, some fully mechanical-in recent years. While a few of these have been commercialized, none have yet met with broad commercial success comparable to the da Vinci robot. In this letter, we suggest a user interface-based explanation for this, and describe a new mechanical instrument that provides wrist articulation with a novel user interface. We provide results of a single-user pilot study with an experienced laparoscopic surgeon to compare the new device with a traditional wristless laparoscopic tool, a prior commercial wristed mechanical tool (the RealHand), and the da Vinci robot, in the context of suturing at challenging angles. We observe better targeting of desired suture needle entry and exit points with the new device in comparison to prior wristed and wristless mechanical instruments, with the da Vinci only slightly outperforming the new tool.