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Lower limb assistive exoskeletons for rehabilitation is a growing field of study. They allow people with spinal cord injuries and strokes to stand upright and walk. Exoskeleton controls research typically focuses on trajectory generation, motion control over the trajectories, and balance and stability. This work focuses on the generalization of people’s joint trajectories climbing a single stair, for an exoskeleton to be developed for people of all leg lengths and be used on variable stair heights. The motion of subjects of different heights, ages, and genders climbing a single stair was collected using motion capture. By using Gaussian mixed regression and Gaussian mixed models, these trajectories were combined to build a model that generalizes individuals with different leg lengths, genders, ages and stair heights. The variability of the subject’s leg length is accounted for by tracking a marker on the toe of the subject and using inverse kinematics to calculate the joint angles. The analysis in this paper shows that joint angles can be generalized to climb various stair heights. In addition, an open-source database of motion capture climbing data and an open-source framework for generating joint trajectories has been made available for public use.

Traditional teleoperation (leader/follower) systems primarily focus on one operator controlling one remote robot, but as robots become ubiquitous, there is an increasing need for multiple operators, including autonomous agents, to collaboratively control multiple robots. However, existing teleoperation frameworks do not inherently support the variety of possible collaborations, such as multiple operators, each with an input device (leader), controlling a robot and camera or different degrees of freedom of a single robot (follower). The same concept applies to teleoperating robots in a simulation environment through physical input devices. In this letter, we extend our novel simulation framework that is capable of incorporating multiple input devices asynchronously with a real-time dynamic simulation to incorporate a customizable shared control. For this purpose, we have identified and implemented a sufficient set of coordinate frames to encapsulate the pairing of multiple leaders, followers and cameras in a shared asynchronous manner with force feedback. We demonstrate the utility of this framework in accelerating user training, ease of learning, and enhanced task completion times through shared control by a supervisor.

Objective: Treatment of brain tumors requires high precision in order to ensure sufficient treatment while minimizing damage to surrounding healthy tissue. Ablation of such tumors using needle-based therapeutic ultrasound (NBTU) under real-time magnetic resonance imaging (MRI) can fulfill this need. However, the constrained space and strong magnetic field in the MRI bore restricts patient access limiting precise placement of the NBTU ablation tool. A surgical robot compatible with use inside the bore of an MRI scanner can alleviate these challenges. Methods: We present preclinical trials of a robotic system for NBTU ablation of brain tumors under real-time MRI guidance. The system comprises of an updated robotic manipulator and corresponding control electronics, the NBTU ablation system and applications for planning, navigation and monitoring of the system. Results: The robotic system had a mean translational and rotational accuracy of 1.39 $\pm$ 0.64 mm and 1.27 $\pm \;\text{0.56}^{\circ }$ in gelatin phantoms and 3.13 $\pm$ 1.41 mm and 5.58 $\pm \;\text{3.59}^{\circ }$ in 10 porcine trials while causing a maximum reduction in signal to noise ratio (SNR) of 10.3%. Conclusion: The integrated robotic system can place NBTU ablator at a desired target location in porcine brain and monitor the ablation in realtime via magnetic resonance thermal imaging (MRTI). Significance: Further optimization of this system could result in a clinically viable system for use in human trials for various diagnostic or therapeutic neurosurgical interventions.

Over the past decade, wearable robotics and exoskeletons have been gaining recognition in the field of medical, assistive and augmentative robotics and have led to numerous new innovative mechanisms and designs. Due to fast-paced research activities, the critical importance and performance of established mechanisms such as wrap spring clutch/brake, Wafer Disc Brakes have been overlooked or used ineffectively. This paper describes a practical design approach that will enable the designer to choose a mechanism based on the application of the device, which will promote overall growth in current technology. The Legged Anthropomorphic Robotic Rehabilitation Exoskeleton (LARRE) project used this approach to design, manufacture, and test the knee joint for ground-level walking. This paper provides the reasoning behind the selection of wrap spring clutch, its evaluation, and testing standards as the knee joint. A thorough literature review was conducted to understand the current state of the art. This project collected a rich set of biomechanical data to ensure that the mechanism will produce the right moments and range of motions during walking. To ensure that our mechanism meets the requirements, the mechanism was put through a wide range of stress tests. The paper establishes a methodology to choose a mechanism for an exoskeleton’s joint based on the desired requirements. The outcome of this paper is an analytical based design approach that can be used by other researchers to impart additional traits and weights, which will aid in the development of exoskeleton design.

An essential step toward commercializing engineered tissues is to scale-up and automate their production. This presents a challenge for self-assembled tissues that are fragile at early time points and difficult to handle using robotic systems. The goal of this study was to automate tissue-engineered blood vessel (TEBV) fabrication by creating a custom cell seeding and self-assembly system that is conducive to robotic manipulation, coupled with a robotic system to assemble smooth muscle cell ring units into tissue tubes. To generate self-assembled tissue ring units manually, cells are seeded at a high density into custom agarose wells that have center posts (2 mm inner diameter), around which cells aggregate and contract to form rings. Agarose is well-suited for cell seeding and ring self-assembly because it is noncell adhesive, can be autoclaved, and reproducibly cast to form wells using silicone templates. However, agarose gel is soft and makes reliable robotic manipulation challenging. To solve this problem, we designed a custom ring self-assembly plate utilizing polyetherimide (PEI) wells with MED610 three-dimensional-printed center posts and an MED610 well negative that allows the casting of individual, annular agarose cell-seeding troughs within the PEI plate. Rings cultured in the new plate system were morphologically similar to rings cultured in control agarose wells and had a slightly higher failure load. To automate tube assembly, we created a unique robotic punch system to push tissue rings out of the PEI-MED610 plate onto a stainless steel mandrel to enable tube fusion. Tubes fabricated by manual or robotic ring removal and placement demonstrated similar morphology after tube fusion, and the automated system substantially reduced the time required to assemble tubes. In summary, we developed a novel robotic assembly system to precisely manipulate self-assembled tissue rings and enable scale-up and automation of TEBV biofabrication. IMPACT STATEMENT: Self-assembled tissues have potential to serve both as implantable grafts and as tools for disease modeling and drug screening. For these applications, tissue production must ultimately be scaled-up and automated. Limited technologies exist for precisely manipulating self-assembled tissues, which are fragile early in culture. Here, we presented a method for automatically stacking self-assembled smooth muscle cell rings onto mandrels, using a custom-designed well plate and robotic punch system. Rings then fuse into tissue-engineered blood vessels (TEBVs). This is a critical step toward automating TEBV production that may be applied to other tubular tissues as well.

Robot-assisted minimally invasive surgery has made a substantial impact in operating rooms over the past few decades with their high dexterity, small tool size, and impact on adoption of minimally invasive techniques. In recent years, intelligence and different levels of surgical robot autonomy have emerged thanks to the medical robotics endeavors at numerous academic institutions and leading surgical robot companies. To accelerate interaction within the research community and prevent repeated development, we propose the Collaborative Robotics Toolkit (CRTK), a common API for the RAVEN-II and da Vinci Research Kit (dVRK) - two open surgical robot platforms installed at more than 40 institutions worldwide. CRTK has broadened to include other robots and devices, including simulated robotic systems and industrial robots. This common API is a community software infrastructure for research and education in cutting edge human-robot collaborative areas such as semi-autonomous teleoperation and medical robotics. This paper presents the concepts, design details and the integration of CRTK with physical robot systems and simulation platforms.

The recent development of Robot-Assisted Minimally Invasive Surgery (RAMIS) has brought much benefit to ease the performance of complex Minimally Invasive Surgery (MIS) tasks and lead to more clinical outcomes. Compared to direct master-slave manipulation, semi-autonomous control for the surgical robot can enhance the efficiency of the operation, particularly for repetitive tasks. However, operating in a highly dynamic in-vivo environment is complex. Supervisory control functions should be included to ensure flexibility and safety during the autonomous control phase. This paper presents a haptic rendering interface to enable supervised semi-autonomous control for a surgical robot. Bayesian optimization is used to tune user-specific parameters during the surgical training process. User studies were conducted on a customized simulator for validation. Detailed comparisons are made between with and without the supervised semi-autonomous control mode in terms of the number of clutching events, task completion time, master robot end-effector trajectory and average control speed of the slave robot. The effectiveness of the Bayesian optimization is also evaluated, demonstrating that the optimized parameters can significantly improve users' performance. Results indicate that the proposed control method can reduce the operator's workload and enhance operation efficiency.

Over the past decade, Robot-Assisted Surgeries (RAS), have become more prevalent in facilitating successful operations. Of the various types of RAS, the domain of collaborative surgery has gained traction in medical research. Prominent examples include providing haptic feedback to sense tissue consistency, and automating sub-tasks during surgery such as cutting or needle hand-off - pulling and reorienting the needle after insertion during suturing. By fragmenting suturing into automated and manual tasks the surgeon could essentially control the process with one hand and also circumvent workspace restrictions imposed by the control interface present at the surgeon's side during the operation. This paper presents an exploration of a discrete reinforcement learning-based approach to automate the needle hand-off task. Users were asked to perform a simple running suture using the da Vinci Research Kit. The user trajectory was learnt by generating a sparse reward function and deriving an optimal policy using Q-learning. Trajectories obtained from three learnt policies were compared to the user defined trajectory. The results showed a root-mean-square error of [0.0044mm, 0.0027mm, 0.0020mm] in ℝ3. Additional trajectories from varying initial positions were produced from a single policy to simulate repeated passes of the hand-off task.

We present an open-source framework that provides a low barrier to entry for real-time simulation, visualization, and interactive manipulation of user-specifiable soft-bodies, environments, and robots (using a human-readable front-end interface). The simulated soft-bodies can be interacted by a variety of input interface devices including commercially available haptic devices, game controllers, and the Master Tele-Manipulators (MTMs) of the da Vinci Research Kit (dVRK) with real-time haptic feedback. We propose this framework for carrying out multi-user training, user-studies, and improving the control strategies for manipulation problems. In this paper, we present the associated challenges to the development of such a framework and our proposed solutions. We also demonstrate the performance of this framework with examples of soft-body manipulation and interaction with various input devices.

Surgical robots for laparoscopy consist of several patient side slave manipulators that are controlled via surgeon operated master telemanipulators. Commercial surgical robots do not perform any sub-tasks – even of repetitive or noninvasive nature – autonomously or provide intelligent assistance. While this is primarily due to safety and regulatory reasons, the state of such automation intelligence also lacks the reliability and robustness for use in high-risk applications. Recent developments in continuous control using Artificial Intelligence and Reinforcement Learning have prompted growing research interest in automating mundane sub-tasks. To build on this, we present an inspired Asynchronous Framework which incorporates realtime dynamic simulation – manipulable with the masters of a surgical robot and various other input devices – and interfaces with learning agents to train and potentially allow for the execution of shared sub-tasks. The scope of this framework is generic to cater to various surgical (as well as non-surgical) training and control applications. This scope is demonstrated by examples of multi-user and multi-manual applications which allow for realistic interactions by incorporating distributed control, shared task allocation and a well-defined communication pipe-line for learning agents. These examples are discussed in conjunction with the design philosophy, specifications, system-architecture and metrics of the Asynchronous Framework and the accompanying Simulator. We show the stability of Simulator while achieving real-time dynamic simulation and interfacing with several haptic input devices and a training agent at the same time.

The da Vinci Research Kit (dVRK) is a teleoperated surgical robotic system. For dynamic simulations and model-based control, the dynamic model of the dVRK is required. We present an open-source dynamic model identification package for the dVRK, capable of modeling the parallelograms, springs, counterweight, and tendon couplings, which are inherent to the dVRK. A convex optimization-based method is used to identify the dynamic parameters of the dVRK subject to physical consistency. Experimental results show the effectiveness of the modeling and the robustness of the package. Although this software package is originally developed for the dVRK, it is feasible to apply it on other similar robots., 8 pages, in IEEE Robotics and Automation Letters., 2019

Intra-operative imaging is sometimes available to assist needle biopsy, but typical open-loop insertion does not account for unmodeled needle deflection or target shift. Closed-loop image-guided compensation for deviation from an initial straight-line trajectory through rotational control of an asymmetric tip can reduce targeting error. Incorporating robotic closed-loop control often reduces physician interaction with the patient, but by pairing closed-loop trajectory compensation with hands-on cooperatively controlled insertion, a physician’s control of the procedure can be maintained while incorporating benefits of robotic accuracy. A series of needle insertions were performed with a typical 18G needle using closed-loop active compensation under both fully autonomous and user-directed cooperative control. We demonstrated equivalent improvement in accuracy while maintaining physician-in-the-loop control with no statistically significant difference (p > 0.05) in the targeting accuracy between any pair of autonomous or individual cooperative sets, with average targeting accuracy of 3.56 mm(rms). With cooperatively controlled insertions and target shift between 1 mm – 10 mm introduced upon needle contact, the system was able to effectively compensate up to the point where error approached a maximum curvature governed by bending mechanics. These results show closed-loop active compensation can enhance targeting accuracy, and that the improvement can be maintained under user directed cooperative insertion.

In this paper, we propose an authentication approach based on the uniqueness of the biomechanics of finger movements. We use an optical-marker-based motion-capture as a preliminary setup to capture goniometric (joint-related) and dermatologic (skin-related) features from the flexion and extension of the index and middle fingers of a subject. We use this information to build a personalized authentication model for a given subject. Analysis of our approach using finger motion-capture from 8 subjects, using reflective tracking markers placed around the joints of index and middle fingers of the subjects shows its viability. In this preliminary study, we achieve an average equal error rate (EER)—when false accept rate and false reject rate are equal—of 6.3% in authenticating a subject immediately after training the authentication model and 16.4% ERR after a week.

This article demonstrates on the use of closed-loop surgery methods in magnetic resonance imaging (MRI). MRI is a highly effective soft tissue imaging system, and the ability to utilize this procedure in-vivo coupled with precision computer controlled motion will prove to be an invaluable asset in the future development of minimally invasive surgery. Robotic assistance has been investigated for guiding instrument placement in MRI, beginning with neurosurgery and later percutaneous interventions with some examples shown in the paper. In order for a system to compatible with the MRI environment, it should: be safe in the MRI environment, preserve the image quality, and be able to operate unaffected by the scanner’s electric and magnetic fields. Closed loop control requires multiple levels of feedback. Optical encoders have proven to be successful for position sensing inside the scanner bore during imaging when coupled with differential line drivers, filtering appropriate electrical lines, and thoroughly shielding cables to minimize electromagnetic interference (EMI).

Background Robot-assisted minimally-invasive surgery is well recognized as a feasible solution for diagnosis and treatment of prostate cancer in humans. Methods This paper discusses the kinematics of a parallel 4 Degrees-of-Freedom (DOF) surgical manipulator designed for minimally invasive in-bore prostate percutaneous interventions through the patient's perineum. The proposed manipulator takes advantage of four sliders actuated by MRI-compatible piezoelectric motors and incremental rotary encoders. Errors, mostly originating from the design and manufacturing process, need to be identified and reduced before the robot is deployed in clinical trials. Results The manipulator has undergone several experiments to evaluate the repeatability and accuracy (about 1 mm in air (in x or y direction) at the needle's reference point) of needle placement, which is an essential concern in percutaneous prostate interventions. Conclusion The acquired results endorse the sustainability, precision and reliability of the manipulator. Copyright © 2015 John Wiley & Sons, Ltd.

The use of magnetic resonance imaging (MRI) for guiding robotic surgical devices has shown great potential for performing precisely targeted and controlled interventions. To fully realize these benefits, devices must work safely within the tight confines of the MRI bore without negatively impacting image quality. Here we expand on previous work exploring MRI guided robots for neural interventions by presenting the mechanical design and assessment of a device for positioning, orienting, and inserting an interstitial ultrasound-based ablation probe. From our previous work we have added a 2 degree of freedom (DOF) needle driver for use with the aforementioned probe, revised the mechanical design to improve strength and function, and performed an evaluation of the mechanism’s accuracy and effect on MR image quality. The result of this work is a 7-DOF MRI robot capable of positioning a needle tip and orienting it’s axis with accuracy of 1.37 ± 0.06mm and 0.79° ± 0.41°, inserting it along it’s axis with an accuracy of 0.06 ± 0.07mm, and rotating it about it’s axis to an accuracy of 0.77° ± 1.31°. This was accomplished with no significant reduction in SNR caused by the robot’s presence in the MRI bore, ≤ 10.3% reduction in SNR from running the robot’s motors during a scan, and no visible paramagnetic artifacts.

Printed and/or digital atlases are important tools for medical research and surgical intervention. While these atlases can provide guidance in identifying anatomical structures, they do not take into account the wide variations in the shape and size of anatomical structures that can occur from patient to patient. Accurate, patient-specific representations are especially important for surgical interventions like deep brain stimulation, where even small inaccuracies can result in dangerous complications. This research effort extends the discrete deformable 2-simplex mesh into the multi-material domain where geometry-based internal forces and image-based external forces are used in the deformation process. Multi-material 2-simplex meshes having shared boundaries are initialized from multi-material triangular surface meshes. A multi-material deformable framework is presented and used to segment anatomical structures of the deep brain region such as the subthalamic nucleus.

This paper presents the development, preclinical evaluation, and preliminary clinical study of a robotic system for targeted transperineal prostate biopsy under direct interventional magnetic resonance imaging (MRI) guidance. The clinically integrated robotic system is developed based on a modular design approach, comprised of surgical navigation application, robot control software, MRI robot controller hardware, and robotic needle placement manipulator. The system provides enabling technologies for MRI-guided procedures. It can be easily transported and setup for supporting the clinical workflow of interventional procedures, and the system is readily extensible and reconfigurable to other clinical applications. Preclinical evaluation of the system is performed with phantom studies in a 3 Tesla MRI scanner, rehearsing the proposed clinical workflow, and demonstrating an in-plane targeting error of 1.5[Formula: see text]mm. The robotic system has been approved by the institutional review board (IRB) for clinical trials. A preliminary clinical study is conducted with the patient consent, demonstrating the targeting errors at two biopsy target sites to be 4.0[Formula: see text]mm and 3.7[Formula: see text]mm, which is sufficient to target a clinically significant tumor foci. First-in-human trials to evaluate the system’s effectiveness and accuracy for MR image-guided prostate biopsy are underway.

This paper presents the design, modeling and experimental evaluation of a magnetic resonance imaging (MRI)-compatible concentric tube continuum robotic system. This system enables MRI-guided deployment of a precurved and steerable concentric tube continuum mechanism, and is suitable for clinical applications where a curved trajectory is needed. This compact 6 degree-of-freedom (DOF) robotic system is piezoelectrically-actuated, and allows simultaneous robot motion and imaging with no visually observable image artifact. The targeting accuracy is evaluated with optical tracking system and gelatin phantom under live MRI-guidance with Root Mean Square (RMS) errors of 1.94 and 2.17 mm respectively. Furthermore, we demonstrate that the robot has kinematic redundancy to reach the same target through different paths. This was evaluated in both free space and MRI-guided gelatin phantom trails, with RMS errors of 0.48 and 0.59 mm respectively. As the first of its kind, MRI-guided targeted concentric tube needle placements with ex vivo porcine liver are demonstrated with 4.64 mm RMS error through closed-loop control of the piezoelectrically-actuated robot.

A software system to provide intuitive navigation for MRI-guided robotic transperineal prostate therapy is presented. In the system, the robot control unit, the MRI scanner, and the open-source navigation software are connected together via Ethernet to exchange commands, coordinates, and images using an open network communication protocol, OpenIGTLink. The system has six states called “workphases” that provide the necessary synchronization of all components during each stage of the clinical workflow, and the user interface guides the operator linearly through these workphases. On top of this framework, the software provides the following features for needle guidance: interactive target planning; 3D image visualization with current needle position; treatment monitoring through real-time MR images of needle trajectories in the prostate. These features are supported by calibration of robot and image coordinates by fiducial-based registration. Performance tests show that the registration error of the system was 2.6 mm within the prostate volume. Registered real-time 2D images were displayed 1.97 s after the image location is specified.

Background With increasing research on system integration for imageguided therapy (IGT), there has been a strong demand for standardized communication among devices and software to share data such as target positions, images and device status.

Magnetic Resonance Imaging (MRI) offers great potential for planning, guiding, monitoring and controlling interventions. MR arthrography (MRAr) is the imaging gold standard for assessing small ligament and fibrocartilage injury in joints. In contemporary practice, MRAr consists of two consecutive sessions: (1) an interventional session where a needle is driven to the joint space and MR contrast is injected under fluoroscopy or CT guidance; and (2) a diagnostic MRI imaging session to visualize the distribution of contrast inside the joint space and evaluate the condition of the joint. Our approach to MRAr is to eliminate the separate radiologically guided needle insertion and contrast injection procedure by performing those tasks on conventional high-field closed MRI scanners. We propose a 2D augmented reality image overlay device to guide needle insertion procedures. This approach makes diagnostic high-field magnets available for interventions without a complex and expensive engineering entourage. In preclinical trials, needle insertions have been performed in the joints of porcine and human cadavers using MR image overlay guidance; in all cases, insertions successfully reached the joint space on the first attempt.

We present an image overlay system to aid needle insertion procedures in computed tomography (CT) scanners. The device consists of a display and a semitransparent mirror that is mounted on the gantry. Looking at the patient through the mirror, the CT image appears to be floating inside the patient with correct size and position, thereby providing the physician with two-dimensional (2-D) "X-ray vision" to guide needle insertions. The physician inserts the needle following the optimal path identified in the CT image rendered on the display and, thus, reflected in the mirror. The system promises to reduce X-ray dose, patient discomfort, and procedure time by significantly reducing faulty insertion attempts. It may also increase needle placement accuracy. We report the design and implementation of the image overlay system followed by the results of phantom and cadaver experiments in several clinical applications.

We present a telerobotics research platform that provides complete access to all levels of control via open- source electronics and software. The electronics employs an FPGA to enable a centralized computation and distributed I/O architecture in which all control computations are implemented in a familiar development environment (Linux PC) and low- latency I/O is performed over an IEEE-1394a (FireWire) bus at speeds up to 400 Mbits/sec. The mechanical components are obtained from retired first-generation da Vinci R Surgical Systems. This system is currently installed at 11 research institutions, with additional installations underway, thereby creating a research community around a common open-source hardware and software platform.

Intra-operative medical imaging enables incorporation of human experience and intelligence in a controlled, closed-loop fashion. Magnetic resonance imaging (MRI) is an ideal modality for surgical guidance of diagnostic and therapeutic procedures, with its ability to perform high resolution, real-time, high soft tissue contrast imaging without ionizing radiation. However, for most current image-guided approaches only static pre-operative images are accessible for guidance, which are unable to provide updated information during a surgical procedure. The high magnetic field, electrical interference, and limited access of closed-bore MRI render great challenges to developing robotic systems that can perform inside a diagnostic high-field MRI while obtaining interactively updated MR images. To overcome these limitations, we are developing a piezoelectrically actuated robotic assistant for actuated percutaneous prostate interventions under real-time MRI guidance. Utilizing a modular design, the system enables coherent and straight forward workflow for various percutaneous interventions, including prostate biopsy sampling and brachytherapy seed placement, using various needle driver configurations. The unified workflow compromises: 1) system hardware and software initialization, 2) fiducial frame registration, 3) target selection and motion planning, 4) moving to the target and performing the intervention (e.g. taking a biopsy sample) under live imaging, and 5) visualization and verification. Phantom experiments of prostate biopsy and brachytherapy were executed under MRI-guidance to evaluate the feasibility of the workflow. The robot successfully performed fully actuated biopsy sampling and delivery of simulated brachytherapy seeds under live MR imaging, as well as precise delivery of a prostate brachytherapy seed distribution with an RMS accuracy of 0.98mm.

Magnetic resonance imaging (MRI) provides high resolution multi-parametric imaging, large soft tissue contrast, and interactive image updates making it an ideal modality for diagnosing prostate cancer and guiding surgical tools. Despite a substantial armamentarium of apparatuses and systems has been developed to assist surgical diagnosis and therapy for MRI-guided procedures over last decade, the unified method to develop high fidelity robotic systems in terms of accuracy, dynamic performance, size, robustness and modularity, to work inside close-bore MRI scanner still remains a challenge. In this work, we develop and evaluate an integrated modular hardware and software system to support the surgical workflow of intra-operative MRI, with percutaneous prostate intervention as an illustrative case. Specifically, the distinct apparatuses and methods include: 1) a robot controller system for precision closed loop control of piezoelectric motors, 2) a robot control interface software that connects the 3D Slicer navigation software and the robot controller to exchange robot commands and coordinates using the OpenIGTLink open network communication protocol, and 3) MRI scan plane alignment to the planned path and imaging of the needle as it is inserted into the target location. A preliminary experiment with ex-vivo phantom validates the system workflow, MRI-compatibility and shows that the robotic system has a better than 0.01mm positioning accuracy.

This paper presents the design of a haptic system for prostate needle brachytherapy under magnetic resonance imaging (MRI) guidance. This haptic system consists of some recently developed MRI-compatible mechatronic devices, including a fiber optic force sensor and a piezoelectric motor actuated needle driver mounted on a specifically designed 3-axis linear stage. We first propose the teleoperation framework with system architecture, infrastructure and control algorithm for the master-slave haptic interface. Then we introduce some novel sensors and actuators for MRI-compatible mechatronic devices of this haptic system. We developed the force sensor which provides in-vivo measurement of needle insertion forces to render proprioception associated with the brachytherapy procedure. We discuss the sensing principle of the optical sensor which enables two degrees-of-freedom (DOF) torque measurement and one DOF force measurement. The second apparatus of this system is a high precision 3-axis linear stage actuated by piezoelectric motors and position sensed by optical linear and rotary encoders and all of them have proved good magnetic compatibility. The needle driver can simultaneously provide needle cannula rotation and stylet translation motion while the cannula translation is engendered by the stage. The independent rotation and translation motion of the cannula and stylet can increase the targeting accuracy while minimize the tissue deformation and damage. The master-slave haptic system is capable of positioning needle and sensing insertion forces thus increasing the operation autonomy, accuracy and reducing the operation time.

The work presented in this paper has been performed in furtherance of developing an MRI (Magnetic resonance imaging) compatible fiber optical force sensor. In this paper, we discuss the design criteria and sensing principle of this optical sensor for monitoring forces in the 0–20 Newton range with an sub-Newton resolution. This instrumentation enables two degrees-of-freedom (DOF) torque measurement and one DOF force measurement. A novel flexure mechanism is designed and the finite element analysis is performed to aid the optimization of the design parameters. This 3 axis force/torque sensor with this range and resolution is an ideal tool for interventional procedures, e.g. needle biopsy and brachytherapy. The sensor is experimentally investigated and calibrated. Calibration results demonstrate that this sensor is a practical and accurate measurement apparatus.

Prostate cancer biopsy is a routine medical procedure, yet conventional techniques suffer from low sensitivity attributed to suboptimal image guidance and needle placement. Targeting small lesions and foci (5 mm in diameter) is particularly prone to errors. We developed an integrated system to perform robot-assisted transperineal needle insertions into the prostate, under Magnetic Resonance Imaging (MRI) guidance. The system provides arbitrary needle trajectories and allows for simultaneous surveillance and correction of the needle path, based on intra-operative MRI. System functionality and data transfer and processing tests were conducted. Five lesions embedded in the gel phantom were targeted successfully, while communication delays (due to higher image frame rates) had no adverse affect on robot-software communication. The system was sufficiently resistant to high network loads and performed with an acceptable transfer rate.

A software strategy to provide intuitive navigation for MRI-guided robotic transperineal prostate therapy is presented. In the system, the robot control unit, the MRI scanner, and open-source navigation software are connected to one another via Ethernet to exchange commands, coordinates, and images. Six states of the system called "workphases" are defined based on the clinical scenario to synchronize behaviors of all components. The wizard-style user interface allows easy following of the clinical workflow. On top of this framework, the software provides features for intuitive needle guidance: interactive target planning; 3D image visualization with current needle position; treatment monitoring through real-time MRI. These features are supported by calibration of robot and image coordinates by the fiducial-based registration. The performance test shows that the registration error of the system was 2.6 mm in the prostate area, and it displayed real-time 2D image 1.7 s after the completion of image acquisition.

This paper reports an experimental evaluation of the following three different MRI-compatible actuators: a Shinsei ultrasonic motor, a Nanomotion ultrasonic motor and a pneumatic cylinder actuator. We report the results of a study comparing the effect of these actuators on the signal to noise ratio (SNR) of MRI images under a variety of experimental conditions. Evaluation was performed with the controller inside and outside the scanner room and with both 1.5T and 3T MRI scanners. Pneumatic cylinders function with no loss of SNR with controller both inside and outside of the scanner room. The Nanomotion motor performs with moderate loss of SNR when moving during imaging. The Shinsei is unsuitable for motion during imaging. All may be used when motion is appropriately interleaved with imaging cycles.

Gaining access to a surgical site via retracting neighboring tissue can result in complications due to occlusion of the tissue blood supply resulting in ischemic damage. By incorporating oxygenation sensors on the working surfaces of surgical retractors and graspers, it is possible to measure the local tissue oxygen saturation and look for trends in real-time. Further, by measuring tissue interaction forces simultaneously, we can further augment the information available to the surgeon. The sensors provide a means for sensory substitution to help compensate for the decreased sensation present in minimally invasive laparoscopic and robotic procedures that are gaining significant popularity. Sensing surgical instruments will allow for safer and more effective surgeries while not interfering with the normal workflow of a procedure

Numerous studies have demonstrated the efficacy of image-guided needle-based therapy and biopsy in the management of prostate cancer. Magnetic resonance imaging (MRI) is an ideal modality for guiding and monitoring such interventions due to its excellent visualization of the prostate, its sub-structure and surrounding tissues. However, the accuracy of needle placement is limited by image fidelity, needle template guides, needle deflection and tissue deformation. We present a preliminary study of the key sources of needle placement error in actual clinical cases. To address these errors, we have designed a comprehensive robotic assistant system with the following features: high-fidelity MRI imaging, advanced planning and targeting with statistical anatomical atlases and multi-parametric imaging, improved navigation based on direct image feedback, and steady needle placement with a robotic manipulator. The prostate biopsy and brachytherapy procedures are to be performed entirely inside a 3T closed-bore MRI scanner. We present a detailed design of the robotic manipulator and associated planning and targeting systems

Numerous studies have demonstrated the efficacy of image-guided needle-based therapy and biopsy in the management of prostate cancer. Magnetic Resonance Imaging (MRI) is an ideal modality for guiding and monitoring prostatic interventions, due to its excellent visualization of the prostate, its sub-structure and surrounding tissues. Despite these advantages, closed high-field MRI scanners (1.5T or greater) have not typically been used in prostate interventions. The strong magnetic field prevents the use of conventional mechatronics and the confined physical space makes it extremely challenging to access the patient. We have designed a robotic assistant system that overcomes these difficulties and promises safe and reliable intra-prostatic needle placement inside closed high-field MRI scanners. The paper explains the design process, component selection and the system currently being prototyped.

Developing electromagnetically (EM) tracked tools can be very time consuming. Tool design traditionally takes many iterations, each of which requires construction of a physical tool and performing lengthy experiments. We propose a simulator that allows tools to be virtually designed and tested before ever being physically built. Both tool rigid body (RB) configurations and reference RB configurations are configured; the reference RB can be located anywhere in the field, and the tool is virtually moved around the reference in userspecified pattern. Sensor measurements of both RBs are artificially distorted according to a previously acquired error field mapping, and the 6-DOF frames of the Tool and Reference are refit to the distorted sensors. It is possible to predict the tool tip registration error for a particular tool and coordinate reference frame (CRF) in a particular scenario before ever even building the tools.

An image overlay system is presented to assist needle placement in conventional CT scanners. The device consists of a flat LCD display and a half mirror and is mounted on the gantry. Looking at the patient through the mirror, the CT image appears to be floating inside the patient with correct size and position, thereby providing the physician with two-dimensional “X-ray vision” to guide needle placement procedures. The physician inserts the needle following the optimal path identified in the CT image that is rendered on the LCD and thereby reflected in the mirror. The system promises to increase needle placement accuracy and also to reduce X-ray dose, patient discomfort, and procedure time by eliminating faulty insertion attempts. We report cadaver experiments in several clinical applications with a clinically applicable device.

There has been increased interest in minimally invasive ablative treatments that typically require precise placement of the ablator tool to meet the predefined planning and lead to efficient tumor destruction. Standard ablative procedures involve free hand transcutaneous ultrasonography (TCUS) in conjunction with manual tool positioning. Unfortunately, existing TCUS systems suffer from many limitations and result in failure to identify nearly half of all treatable liver lesions. Freehand manipulation of the ultrasound (US) probe and ablator tool lacks the critical level of control, accuracy, stability, and guaranteed performance required for these procedures. Freehand US results in undefined gap distribution, anatomic deformation due to variable pressure from the sonographer's hand, and severe difficulty in maintaining optimal scanning position. In response to these limitations, we propose the use of a dual robotic arm system that manages both ultrasound manipulation and needle guidance. We report a prototype of the dual arm system and a comparative performance analysis between robotic vs. freehand systems, for both US scanning and needle placement in mechanical and animal tissue phantoms.

Minimally Invasive Surgery (MIS) has enjoyed increasing attention and development over the last two decades. As MIS systems evolve, the surgeon is increasingly insulated from patient contact, creating a trade-off between surgi- cal sensory information and patient invasiveness. Incorporation of haptic feed- back into MIS systems promises to restore sensory information surrendered in favor of minimal invasiveness. We have developed a novel, biocompatible 2- DOF force-sensing sleeve that can be used modularly with a variety of 5mm laparoscopic instruments. The functional requirements for such a device are de- fined, and design strategies are explored. Our formal device design is outlined and device calibration is presented with derived calibration functions. Illustrative experimental force data from a porcine model is presented. This device can be used for intra-abdominal force recording and feedback in laparoscopic environ- ments; the implications and future potential for this technology are explored.