Control and Estimation Methods Towards Safe Robot-assisted Eye Surgery

Vitreoretinal surgery is among the most delicate surgical tasks in which physiological hand tremor may severely diminish surgeon performance and put the eye at high risk of injury. Unerring targeting accuracy is required to perform precise operations on micro-scale tissues. Tool tip to tissue interaction forces are usually below human tactile perception, which may result in exertion of excessive forces to the retinal tissue leading to irreversible damages. Notable challenges during retinal surgery lend themselves to robotic assistance which has proven beneficial in providing a safe steady-hand manipulation. Efficient assistance from the robots heavily relies on accurate sensing and intelligent control algorithms of important surgery states and situations (e.g. instrument tip position measurements and control of interaction forces). This dissertation provides novel control and state estimation methods to improve safety during robot-assisted eye surgery. The integration of robotics into retinal microsurgery leads to a reduction in surgeon perception of tool-to-tissue forces at sclera. This blunting of human tactile sensory input, which is due to the inflexible inertia of the robot, is a potential iatrogenic risk during robotic eye surgery. To address this issue, a sensorized surgical instrument equipped with Fiber Bragg Grating (FBG) sensors, which is capable of measuring the sclera forces and instrument insertion depth into the eye, is integrated to the Steady-Hand Eye Robot (SHER). An adaptive control scheme is then customized and implemented on the robot that is intended to autonomously mitigate the risk of unsafe scleral forces and excessive insertion of the instrument. Various preliminary and multi-user clinician studies are then conducted to evaluate the effectiveness of the control method during mock retinal surgery procedures. In addition, due to inherent flexibility and the resulting deflection of eye surgical instruments as well as the need for targeting accuracy, we have developed a method to enhance deflected instrument tip position estimation. Using an iterative method and microscope data, we develop a calibration- and registration-independent (RI) framework to provide online estimates of the instrument stiffness (least squares and adaptive). The estimations are then combined with a state-space model for tip position evolution obtained based on the forward kinematics (FWK) of the robot and FBG sensor measurements. This is accomplished using a Kalman Filtering (KF) approach to improve the instrument tip position estimation during robotic surgery. The entire framework is independent of camera-to-robot coordinate frame registration and is evaluated during various phantom experiments to demonstrate its effectiveness

Non linear force feedback enhancement for cooperative robotic neurosurgery enforces virtual boundaries on cortex surface

Surgeons can benefit from the cooperation with a robotic assistant during the repetitive execution of precise targeting tasks on soft tissues, such as brain cortex stimulation procedures in open-skull neurosurgery. Position-based force-to-motion control schemes may not be satisfactory solution to provide the manipulator with the high compliance desirable during guidance along wide trajectories. A new torque controller with non-linear force feedback enhancement (FFE) is presented to provide augmented haptic perception to the operator from instrument-tissue interaction. Simulation tests were performed to evaluate the system stability according to different non-linear force modulation functions (power, sigmoidal and arc tangent). The FFE controller with power modulation was experimentally validated with a pool of non-expert users using brain-mimicking gelatin phantoms (8%-16% concentration). Besides providing hand tremor rejection for a stable holding of the tool, the FFE controller was proven to allow for a safer tissue contact with respect to both robotic assistance without force feedback and freehand executions (50% and 75% reduction of the indentation depth, respectively). Future work will address the evaluation of the safety features of the FFE controller with expert surgeons on a realistic brain phantom, also accounting for unpredictable tissue's motions as during seizures due to cortex stimulation

Augmentation Of Human Skill In Microsurgery

Surgeons performing highly skilled microsurgery tasks can benefit from information and manual assistance to overcome technological and physiological limitations to make surgery safer, efficient, and more successful. Vitreoretinal surgery is particularly difficult due to inherent micro-scale and fragility of human eye anatomy. Additionally, surgeons are challenged by physiological hand tremor, poor visualization, lack of force sensing, and significant cognitive load while executing high-risk procedures inside the eye, such as epiretinal membrane peeling. This dissertation presents the architecture and the design principles for a surgical augmentation environment which is used to develop innovative functionality to address the fundamental limitations in vitreoretinal surgery. It is an inherently information driven modular system incorporating robotics, sensors, and multimedia components. The integrated nature of the system is leveraged to create intuitive and relevant human-machine interfaces and generate a particular system behavior to provide active physical assistance and present relevant sensory information to the surgeon. These include basic manipulation assistance, audio-visual and haptic feedback, intraoperative imaging and force sensing. The resulting functionality, and the proposed architecture and design methods generalize to other microsurgical procedures. The system's performance is demonstrated and evaluated using phantoms and in vivo experiments

Fiber Bragg Gratings for Medical Applications and Future Challenges: A Review

[EN] In the last decades, fiber Bragg gratings (FBGs) have become increasingly attractive to medical applications due to their unique properties such as small size, biocompatibility, immunity to electromagnetic interferences, high sensitivity and multiplexing capability. FBGs have been employed in the development of surgical tools, assistive devices, wearables, and biosensors, showing great potentialities for medical uses. This paper reviews the FBG-based measuring systems, their principle of work, and their applications in medicine and healthcare. Particular attention is given to sensing solutions for biomechanics, minimally invasive surgery, physiological monitoring, and medical biosensing. Strengths, weaknesses, open challenges, and future trends are also discussed to highlight how FBGs can meet the demands of next-generation medical devices and healthcare system.This work was supported in part by INAIL (the Italian National Institute for Insurance against Accident at Work), through the BRIC (Bando ricerche in collaborazione) 2018 SENSE-RISC (Sviluppo di abiti intelligENti Sensorizzati per prevenzione e mitigazione di Rischi per la SiCurezza dei lavoratori) Project under Grant ID10/2018, in part by the UCBM (Universita Campus Bio-Medico di Roma) under the University Strategic HOPE (HOspital to the PatiEnt) Project, in part by the EU Framework Program H2020-FETPROACT-2018-01 NeuHeart Project under Grant GA 824071, by FCT/MEC (Fundacao para a Ciencia e Tecnologia) under the Projects UIDB/50008/2020 - UIDP/50008/2020, and by REACT (Development of optical fiber solutions for Rehabilitation and e-Health applications) FCT-IT-LA scientific action.Lo Presti, D.; Massaroni, C.; Leitao, CSJ.; Domingues, MDF.; Sypabekova, M.; Barrera, D.; Floris, I.... (2020). Fiber Bragg Gratings for Medical Applications and Future Challenges: A Review. IEEE Access. 8:156863-156888. https://doi.org/10.1109/ACCESS.2020.3019138S156863156888

Optical Coherence Tomography Distal Sensor Based Handheld Microsurgical Tools

Microsurgery is typically differentiated from a general surgery in that it requires a precise sub-millimeter manipulation that could only be achievable under optical magnification. For instance, microsurgeons use surgical microscopes to view surgical sites and train themselves several years to acquire surgical skills to perform the delicate procedures. However, such microsurgical approach imposes considerable physical stress and mental fatigue on the surgeons and these could be sources for surgical risks and complications. For these reasons, a variety of robotic based surgical guidance methods have been developed and studied with the hope of providing safer and more precise microsurgery. These robotic arm based systems have been developed to provide precise tool movement and to remove physiological hand tremor, which is one of the main limiting factors that prevents precise tool manipulation. In another approaches use simpler system that adds robotic functions to existing handheld surgical tools. It is a hybrid system that incorporates the advantages of conventional manual system and robot-assist system. The advantages of such hybrid handheld systems include portability, disposability, and elimination of the large robotic-assist systems in complex surgical environment. The most critical benefit of the hybrid handheld system is its ease of use since it allows surgeons to manipulate tools mostly using their hand. However due to the imprecise nature of tool control using hands, tool tracking is more critical in handheld microsurgical tool systems than that of robotic arm systems. In general, the accuracy of the tool control is largely determined by the resolution of the sensors and the actuators. Therefore, it is essential to develop a real-time high resolution sensor in order to develop a practical microsurgical tools. For this reason, a novel intuitive targeting and tracking scheme that utilizes a common-path swept source optical coherence tomography (CP-SSOCT) distal sensor was developed integrated with handheld microsurgical tools. To achieve micron-order precision control, a reliable and accurate OCT distal sensing method was developed. The method uses a prediction algorithm is necessary to compensate for the system delay associated with the computational, mechanical and electronic latencies. Due to the multi-layered structure of retina, it was also necessary to develop effective surface detection methods rather than simple peak detection. The OCT distal sensor was integrated into handheld motion-guided micro-forceps system for highly accurate depth controlled epiretinal membranectomy. A touch sensor and two motors were used in the forceps design to minimize the motion artifact induced by squeezing, and to independently control the depth guidance of the tool-tip and the grasping action. We also built a depth guided micro-injector system that enables micro-injection with precise injection depth control. For these applications, a smart motion monitoring and a guiding algorithm were developed to provide precise and intuitive freehand control. Finally, phantom and ex-vivo bovine eye experiments were performed to evaluate the performance of the proposed OCT distal sensor and validate the effectiveness of the depth-guided micro-forceps and micro-injector over the freehand performance