A Data-Driven Model with Hysteresis Compensation for I2RIS Robot

Retinal microsurgery is a high-precision surgery performed on an exceedingly delicate tissue. It now requires extensively trained and highly skilled surgeons. Given the restricted range of instrument motion in the confined intraocular space, and also potentially restricting instrument contact with the sclera, snake-like robots may prove to be a promising technology to provide surgeons with greater flexibility, dexterity, space access, and positioning accuracy during retinal procedures requiring high precision and advantageous tooltip approach angles, such as retinal vein cannulation and epiretinal membrane peeling. Kinematics modeling of these robots is an essential step toward accurate position control, however, as opposed to conventional manipulators, modeling of these robots does not follow a straightforward method due to their complex mechanical structure and actuation mechanisms. Especially, in wire-driven snake-like robots, the hysteresis problem due to the wire tension condition can have a significant impact on the positioning accuracy of these robots. In this paper, we proposed an experimental kinematics model with a hysteresis compensation algorithm using the probabilistic Gaussian mixture models (GMM) Gaussian mixture regression (GMR) approach. Experimental results on the two-degree-of-freedom (DOF) integrated robotic intraocular snake (I2RIS) show that the proposed model provides 0.4 deg accuracy, which is an overall 60% and 70% of improvement for yaw and pitch degrees of freedom, respectively, compared to a previous model of this robot

State of the art of robotic surgery related to vision: Brain and eye applications of newly available devices

Raffaele Nuzzi, Luca Brusasco Department of Surgical Sciences, Eye Clinic, University of Torino, Turin, Italy Background: Robot-assisted surgery has revolutionized many surgical subspecialties, mainly where procedures have to be performed in confined, difficult to visualize spaces. Despite advances in general surgery and neurosurgery, in vivo application of robotics to ocular surgery is still in its infancy, owing to the particular complexities of microsurgery. The use of robotic assistance and feedback guidance on surgical maneuvers could improve the technical performance of expert surgeons during the initial phase of the learning curve. Evidence acquisition: We analyzed the advantages and disadvantages of surgical robots, as well as the present applications and future outlook of robotics in neurosurgery in brain areas related to vision and ophthalmology. Discussion: Limitations to robotic assistance remain, that need to be overcome before it can be more widely applied in ocular surgery. Conclusion: There is heightened interest in studies documenting computerized systems that filter out hand tremor and optimize speed of movement, control of force, and direction and range of movement. Further research is still needed to validate robot-assisted procedures. Keywords: robotic surgery related to vision, robots, ophthalmological applications of robotics, eye and brain robots, eye robot

A 5-DOFs Robot for Posterior Segment Eye Microsurgery

In retinal surgery clinicians access the internal volume of the eyeball through small scale trocar ports, typically 0.65 mm in diameter, to treat vitreoretinal disorders like idiopathic epiretinal membrane and age-related macular holes. The treatment of these conditions involves the removal of thin layers of diseased tissue, namely the epiretinal membrane and the internal limiting membrane. These membranes have an average thickness of only 60 μm and 2 μm respectively making extremely challenging even for expert clinicians to peel without damaging the surrounding tissue. In this work we present a novel Ophthalmic microsurgery Robot (OmSR) designed to operate a standard surgical forceps used in these procedures with micrometric precision, overcoming the limitations of current robotic systems associated with the offsetting of the remote centre of motion of the end effector when accessing the sclera. The design of the proposed system is presented, and its performance evaluated. The results show that the end effector can be controlled with an accuracy of less than 30 μm and the surgical forceps opening and closing positional error is less than 4.3 μm. Trajectory-following experiments and membrane peeling experiments are also presented, showing promising results in both scenarios

From teleoperation to autonomous robot-assisted microsurgery: A survey

Robot-assisted microsurgery (RAMS) has many benefits compared to traditional microsurgery. Microsurgical platforms with advanced control strategies, high-quality micro-imaging modalities and micro-sensing systems are worth developing to further enhance the clinical outcomes of RAMS. Within only a few decades, microsurgical robotics has evolved into a rapidly developing research field with increasing attention all over the world. Despite the appreciated benefits, significant challenges remain to be solved. In this review paper, the emerging concepts and achievements of RAMS will be presented. We introduce the development tendency of RAMS from teleoperation to autonomous systems. We highlight the upcoming new research opportunities that require joint efforts from both clinicians and engineers to pursue further outcomes for RAMS in years to come

Toward Improving Safety in Neurosurgery with an Active Handheld Instrument

Microsurgical procedures, such as petroclival meningioma resection, require careful surgical actions in order to remove tumor tissue, while avoiding brain and vessel damaging. Such procedures are currently performed under microscope magnification. Robotic tools are emerging in order to filter surgeons’ unintended movements and prevent tools from entering forbidden regions such as vascular structures. The present work investigates the use of a handheld robotic tool (Micron) to automate vessel avoidance in microsurgery. In particular, we focused on vessel segmentation, implementing a deep-learning-based segmentation strategy in microscopy images, and its integration with a feature-based passive 3D reconstruction algorithm to obtain accurate and robust vessel position. We then implemented a virtual-fixture-based strategy to control the handheld robotic tool and perform vessel avoidance. Clay vascular phantoms, lying on a background obtained from microscopy images recorded during petroclival meningioma surgery, were used for testing the segmentation and control algorithms. When testing the segmentation algorithm on 100 different phantom images, a median Dice similarity coefficient equal to 0.96 was achieved. A set of 25 Micron trials of 80 s in duration, each involving the interaction of Micron with a different vascular phantom, were recorded, with a safety distance equal to 2 mm, which was comparable to the median vessel diameter. Micron’s tip entered the forbidden region 24% of the time when the control algorithm was active. However, the median penetration depth was 16.9 μm, which was two orders of magnitude lower than median vessel diameter. Results suggest the system can assist surgeons in performing safe vessel avoidance during neurosurgical procedures

Force-Sensing-Based Multi-Platform Robotic Assistance for Vitreoretinal Surgery

Vitreoretinal surgery aims to treat disorders of the retina, vitreous body, and macula, such as retinal detachment, diabetic retinopathy, macular hole, epiretinal membrane and retinal vein occlusion. Challenged by several technical and human limitations, vitreoretinal practice currently ranks amongst the most demanding fields in ophthalmic surgery. Of vitreoretinal procedures, membrane peeling is the most common to be performed, over 0.5 million times annually, and among the most prone to complications. It requires an extremely delicate tissue manipulation by various micron scale maneuvers near the retina despite the physiological hand tremor of the operator. In addition, to avoid injuries, the applied forces on the retina need to be kept at a very fine level, which is often well below the tactile sensory threshold of the surgeon. Retinal vein cannulation is another demanding procedure where therapeutic agents are injected into occluded retinal veins. The feasibility of this treatment is limited due to challenges in identifying the moment of venous puncture, achieving cannulation and maintaining it throughout the drug delivery period. Recent advancements in medical robotics have significant potential to address most of the challenges in vitreoretinal practice, and therefore to prevent traumas, lessen complications, minimize intra-operative surgeon effort, maximize surgeon comfort, and promote patient safety. This dissertation presents the development of novel force-sensing tools that can easily be used on various robotic platforms, and robot control methods to produce integrated assistive surgical systems that work in partnership with surgeons against the current limitations in vitreoretinal surgery, specifically focusing on membrane peeling and vein cannulation procedures. Integrating high sensitivity force sensing into the ophthalmic instruments enables precise quantitative monitoring of applied forces. Auditory feedback based upon the measured forces can inform (and warn) the surgeon quickly during the surgery and help prevent injury due to excessive forces. Using these tools on a robotic platform can attenuate hand tremor of the surgeon, which effectively promotes tool manipulation accuracy. In addition, based upon certain force signatures, the robotic system can precisely identify critical instants, such as the venous puncture in retinal vein cannulation, and actively guide the tool towards clinical targets, compensate any involuntary motion of the surgeon, or generate additional motion that will make the surgical task easier. The experimental results using two distinct robotic platforms, the Steady-Hand Eye Robot and Micron, in combination with the force-sensing ophthalmic instruments, show significant performance improvement in artificial dry phantoms and ex vivo biological tissues

Insight into the Design of Aerosol Spray Systems for Cell Therapies for Retinal Diseases using Computational Modelling and Experimental Assessment

Retinal degenerative diseases affect numerous people worldwide and in the UK; they lead to dysfunction of retinal cells and retinal dysfunction, in turn leading to vision loss and in some cases blindness. Existing treatments aim to alleviate current risk factors leading to retinal degeneration, such as increased high pressure. However, these procedures do not restore lost cell, vision nor retinal function, and therefore may still lead to blindness. Developing cell-based therapies to replace lost cells provides one option for retinal tissue repair in order to restore retinal function. These therapies involve delivering stem cells to encourage neural cell-like functions within the retinal tissue. Despite progress in developing stem-cells compatible with the retinal layers, there is also a need to developing a minimal invasive technique for cell delivery, without damaging the neighbouring optical structure. After evaluating several methods of cell delivery, this thesis explores the need for developing aerosol spraying systems for stem-cell delivery into the human eye. Mathematical modelling is used as a tool to define spraying parameters which, alongside experimental work, may accelerate the design of aerosol spraying systems to treat retinal degenerative disease such as glaucoma. Firstly, an organic biomaterial is developed and used as scaffold to spray and protect cells from aerodynamic forces and stresses associated with aerosolization. The rheological properties of this biomaterial are incorporated within a computational model to predict cell-spraying into a human eye. Boundary and initial conditions mimic the experimental spraying conditions, and the parameterised model is used to explore the link between operator-defined conditions (namely volume flow rate of the cell-laden hydrogel, external pressure needed for aerosolization and angle of the spraying) and spraying outputs (surface area of the retina covered, droplets speed, wall shear stress on the retinal surface). Data from both computational and experimental analyses were gathered. Computational modelling is used to explore the impact of spraying parameters (pressure and volume flow rate at the injector nozzle, outer cone angle for the spray) on key outputs of high priority, namely the spatial distribution of the delivered hydrogel on the retinal wall, the surface area of the retina covered and droplet speed. Droplets speed at the retinal wall appeared to increase with increasing pressure conditions and were observed at a constant volume flow rate. Experimental assessments were used to validate the computational data and determine cell viability under set environmental conditions (external pressure and volume flow rate of cell-laden hydrogel) through in-vitro testing. This thesis defines indicative spraying parameters for delivering therapeutic cells to the human retina, based on a combination of computational modelling and experimental studies. Mathematical modelling provides the potential to transfer these findings to other organ systems, aligning with broader effects to develop cell delivery systems to treat organ disease and repair