Retinal surgeons are required to manipulate multiple surgical instruments in a confined intraocular space, while the instruments are constrained at the small incisions made on the sclera. Furthermore, physiological hand tremor can affect the precision of the instrument motion. The Steady-Hand Eye Robot (SHER), developed in our previous study, enables tremor-free tool manipulation by employing a cooperative control scheme whereby the surgeon and robot can co-manipulate the surgical instruments. Although SHER enables precise and tremor-free manipulation of surgical tools, its straight and rigid structure imposes certain limitations, as it can only approach a target on the retina from one direction. As a result, the instrument could potentially collide with the eye lens when attempting to access the anterior portion of the retina. In addition, it can be difficult to approach a target on the retina from a suitable direction when accessing its anterior portion for procedures such as vein cannulation or membrane peeling. Snake-like robots offer greater dexterity and allow access to a target on the retina from suitable directions, depending on the clinical task at hand. In this study, we present an integrated, high-dexterity, cooperative robotic assistant for intraocular micromanipulation. This robotic assistant comprises an improved integrated robotic intraocular snake (I2RIS) with a user interface (a tactile switch or joystick unit) for the manipulation of the snake-like distal end and the SHER, with a detachable end-effector to which the I2RIS can be attached. The integrated system was evaluated through a set of experiments wherein subjects were requested to touch or insert into randomly-assigned targets. The results indicate that the high-dexterity robotic assistant can touch or insert the tip into the same target from multiple directions, with no significant increase in task completion time for either user interface.

This paper reports the development of a fully actuated body-mounted robotic assistant for MRI-guided low back pain injection. The robot is designed with a 4-DOF needle alignment module and a 2-DOF remotely actuated needle driver module. The 6-DOF fully actuated robot can operate inside the scanner bore during imaging; hence, minimizing the need of moving the patient in or out of the scanner during the procedure, and thus potentially reducing the procedure time and streamlining the workflow. The robot is built with a lightweight and compact structure that can be attached directly to the patient's lower back using straps; therefore, attenuating the effect of patient motion by moving with the patient. The novel remote actuation design of the needle driver module with beaded chain transmission can reduce the weight and profile on the patient, as well as minimize the imaging degradation caused by the actuation electronics. The free space positioning accuracy of the system was evaluated with an optical tracking system, demonstrating the mean absolute errors (MAE) of the tip position to be 0.99±0.46 mm and orientation to be 0.99±0.65°. Qualitative imaging quality evaluation was performed on a human volunteer, revealing minimal visible image degradation that should not affect the procedure. The mounting stability of the system was assessed on a human volunteer, indicating the 3D position variation of target movement with respect to the robot frame to be less than 0.7 mm.

Robot-assisted retinal surgery has become increasingly prevalent in recent years in part due to the potential for robots to help surgeons improve the safety of an immensely delicate and difficult set of tasks. The integration of robots into retinal surgery has resulted in diminished surgeon perception of tool-to-tissue interaction forces due to robot's stiffness. The tactile perception of these interaction forces (sclera force) has long been a crucial source of feedback for surgeons who rely on them to guide surgical maneuvers and to prevent damaging forces from being applied to the eye. This problem is exacerbated when there are unfavorable sclera forces originating from patient movements (dynamic eyeball manipulation) during surgery which may cause the sclera forces to increase even drastically. In this study we aim at evaluating the efficacy of providing warning auditory feedback based on the level of sclera force measured by force sensing instruments. The intent is to enhance safety during dynamic eye manipulations in robot-assisted retinal surgery. The disturbances caused by lateral movement of patient's head are simulated using a piezo-actuated linear stage. The Johns Hopkins Steady-Hand Eye Robot (SHER), is then used in a multi-user experiment. Twelve participants are asked to perform a mock retinal surgery by following painted vessels inside an eye phantom using a force sensing instrument while auditory feedback is provided. The results indicate that the users are able to handle the eye motion disturbances while maintaining the sclera forces within safe boundaries when audio feedback is provided.

Robot-assisted vitreoretinal surgery can filter surgeons' hand tremors and provide safe, accurate tool manipulation. In this paper, we report the design, optimization, and evaluation of a novel tilt mechanism for a new Steady-Hand Eye Robot (SHER). The new tilt mechanism features a four-bar linkage design and has a compact structure. Its kinematic configuration is optimized to minimize the required linear range of motion (LRM) for implementing a virtual remote center-of-motion (V-RCM) while tilting a surgical tool. Due to the different optimization constraints for the robots at the left and right sides of the human head, two configurations of this tilt mechanism are proposed. Experimental results show that the optimized tilt mechanism requires a significantly smaller LRM (e.g. 5.08 mm along Z direction and 8.77 mm along Y direction for left side robot) as compared to the slider-crank tilt mechanism used in the previous SHER (32.39 mm along Z direction and 21.10 mm along Y direction). The feasibility of the proposed tilt mechanism is verified in a mock bilateral robot-assisted vitreoretinal surgery. The ergonomically acceptable robot postures needed to access the surgical field is also determined.

One of the significant challenges of moving from manual to robot-assisted retinal surgery is the loss of perception of forces applied to the sclera (sclera forces) by the surgical tools. This damping of force feedback is primarily due to the stiffness and inertia of the robot. The diminished perception of tool-to-eye interactions might put the eye tissue at high risk of injury due to excessive sclera forces or extreme insertion of the tool into the eye. In the present study therefore a 1-dimensional adaptive control method is customized for 3-dimensional control of sclera force components and tool insertion depth and then implemented on the velocity-controlled Johns Hopkins Steady-Hand Eye Robot. The control method enables the robot to perform autonomous motions to make the sclera force and/or insertion depth of the tool tip to follow pre-defined desired and safe trajectories when they exceed safe bounds. A robotic light pipe holding application in retinal surgery is also investigated using the adaptive control method. The implementation results indicate that the adaptive control is able to achieve the imposed safety margins and prevent sclera forces and insertion depth from exceeding safe boundaries.

Retinal microsurgery is technically demanding and requires high surgical skill with very little room for manipulation error. During surgery the tool needs to be inserted into the eyeball while maintaining constant contact with the sclera. Any unexpected manipulation could cause extreme tool-sclera contact force (scleral force) thus damage the sclera. The introduction of robotic assistance could enhance and expand the surgeon's manipulation capabilities during surgery. However, the potential intra-operative danger from surgeon's misoperations remains difficult to detect and prevent by existing robotic systems. Therefore, we propose a method to predict imminent unsafe manipulation in robot-assisted retinal surgery and generate feedback to the surgeon via auditory substitution. The surgeon could then react to the possible unsafe events in advance. This work specifically focuses on minimizing sclera damage using a force-sensing tool calibrated to measure small scleral forces. A recurrent neural network is designed and trained to predict the force safety status up to 500 milliseconds in the future. The system is implemented using an existing "steady hand" eye robot. A vessel following manipulation task is designed and performed on a dry eye phantom to emulate the retinal surgery and to analyze the proposed method. Finally, preliminary validation experiments are performed by five users, the results of which indicate that the proposed early warning system could help to reduce the number of unsafe manipulation events.

In this paper, a novel semi-autonomous control framework is presented for enabling probe-based confocal laser endomicroscopy (pCLE) scan of the retinal tissue. With pCLE, retinal layers such as nerve fiber layer (NFL) and retinal ganglion cell (RGC) can be scanned and characterized in real-time for an improved diagnosis and surgical outcome prediction. However, the limited field of view of the pCLE system and the micron-scale optimal focus distance of the probe, which are in the order of physiological hand tremor, act as barriers to successful manual scan of retinal tissue. Therefore, a novel sensorless framework is proposed for real-time semi-autonomous endomicroscopy scanning during retinal surgery. The framework consists of the Steady-Hand Eye Robot (SHER) integrated with a pCLE system, where the motion of the probe is controlled semi-autonomously. Through a hybrid motion control strategy, the system autonomously controls the confocal probe to optimize the sharpness and quality of the pCLE images, while providing the surgeon with the ability to scan the tissue in a tremor-free manner. Effectiveness of the proposed architecture is validated through experimental evaluations as well as a user study involving 9 participants. It is shown through statistical analyses that the proposed framework can reduce the work load experienced by the users in a statistically-significant manner, while also enhancing their performance in retaining pCLE images with optimized quality.

Retinal surgery involves manipulating very delicate tissues within the confined area of eyeball. In such demanding practices, patient involuntary head movement might abruptly raise tool-to-eyeball interaction forces which would be detrimental to eye. This study is aimed at implementing different force control strategies and evaluating how they contribute to attaining sclera force safety while patient head drift is present. To simulate patient head movement, a piezoelectric-actuated linear stage is used to produce random motions in a single direction in random time intervals. Having an eye phantom attached to the linear stage then an experienced eye surgeon is asked to manipulate the eye and repeat a mock surgical task both with and without the assist of the Steady-Hand Eye Robot. For the freehand case, warning sounds were provided to the surgeon as auditory feedback to alert him about excessive slclra forces. For the robot-assisted experiments two variants of an adaptive sclera force control and a virtual fixture method were deployed to see how they can maintain eye safety under head drift circumstances. The results indicate that the developed robot control strategies are able to compensate for head drift and keep the sclera forces under safe levels as well as the free hand operation.

This paper presents a body-mounted, four degree-of-freedom (4-DOF) parallel mechanism robot for image-guided percutaneous interventions. The design of the robot is optimized to be light weight and compact such that it could be mounted to the patient body. It has a modular design that can be adopted for assisting various image-guided, needle-based percutaneous interventions such as arthrography, biopsy and brachytherapy seed placement. The robot mechanism and the control system are designed and manufactured with components compatible with imaging modalities including Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). The current version of the robot presented in this paper is optimized for shoulder arthrography under MRI guidance; a Z-shaped fiducial frame is attached to the robot, providing accurate and repeatable robot registration with the MR scanner coordinate system. Here we present the mechanical design of the manipulator, robot kinematics, robot calibration procedure, and preliminary bench-top accuracy assessment. The bench-top accuracy evaluation of the robotic manipulator shows average translational error of 1.01 mm and 0.96 mm in X and Z axes, respectively, and average rotational error of 3.06 degrees and 2.07 degrees about the X and Z axes, respectively.

Retinal microsurgery is technically demanding and requires high surgical skill with very little room for manipulation error. The introduction of robotic assistance has the potential to enhance and expand a surgeon's manipulation capabilities during retinal surgery, i.e., improve precision, cancel physiological hand tremor, and provide sensing information. However, surgeon performance may also be negatively impacted by robotic assistance due to robot structural stiffness and nonintuitive controls. In complying with robotic constraints, the surgeon loses the dexterity of the human hand. In this paper, we present a preliminary experimental study to evaluate user behavior when affected by robotic assistance during mock retinal surgery. In these experiments user behavior is characterized by measuring the forces applied by the user to the sclera, the tool insertion/retraction speed, the tool insertion depth relative to the scleral entry point, and the duration of surgery. The users' behavior data is collected during three mock retinal surgery tasks with four users. Each task is conducted using both freehand and robot-assisted techniques. The univariate user behavior and the correlations of multiple parameters of user behavior are analyzed. The results show that robot assistance prolongs the duration of the surgery and increases the manipulation forces applied to sclera, but refines the insertion velocity and eliminates hand tremor.

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.