A Modular 3-Degrees-of-Freedom Force Sensor for Robot-Assisted Minimally Invasive Surgery Research.

Effective force modulation during tissue manipulation is important for ensuring safe, robot-assisted, minimally invasive surgery (RMIS). Strict requirements for in vivo applications have led to prior sensor designs that trade off ease of manufacture and integration against force measurement accuracy along the tool axis. Due to this trade-off, there are no commercial, off-the-shelf, 3-degrees-of-freedom (3DoF) force sensors for RMIS available to researchers. This makes it challenging to develop new approaches to indirect sensing and haptic feedback for bimanual telesurgical manipulation. We present a modular 3DoF force sensor that integrates easily with an existing RMIS tool. We achieve this by relaxing biocompatibility and sterilizability requirements and by using commercial load cells and common electromechanical fabrication techniques. The sensor has a range of ±5 N axially and ±3 N laterally with errors of below 0.15 N and maximum errors below 11% of the sensing range in all directions. During telemanipulation, a pair of jaw-mounted sensors achieved average errors below 0.15 N in all directions. It achieved an average grip force error of 0.156 N. The sensor is for bimanual haptic feedback and robotic force control in delicate tissue telemanipulation. As an open-source design, the sensors can be adapted to suit other non-RMIS robotic applications.

Concepts and Trends n Autonomy for Robot-Assisted Surgery.

Surgical robots have been widely adopted with over 4000 robots being used in practice daily. However, these are telerobots that are fully controlled by skilled human surgeons. Introducing "surgeon-assist"-some forms of autonomy-has the potential to reduce tedium and increase consistency, analogous to driver-assist functions for lanekeeping, cruise control, and parking. This article examines the scientific and technical backgrounds of robotic autonomy in surgery and some ethical, social, and legal implications. We describe several autonomous surgical tasks that have been automated in laboratory settings, and research concepts and trends.

Endoscopic surgery suturing techniques: a randomized study on learning.

BACKGROUND: Surgeons have widely adopted endoscopic suturing techniques using conventional laparoscopic instruments and the more advanced robotic systems. The FlexDex is a novel articulating laparoscopic needle driver providing enhanced dexterity in laparoscopic surgery. This study evaluates and compares the learning curve of endoscopic suturing with conventional laparoscopy, the FlexDex and robotic suturing in novices. METHODS: Participants performed a minimal invasive suturing task in three different ways in a randomized order: with a conventional laparoscopic needle driver, using the FlexDex needle driver and third, using the Da Vinci Si surgical system. Primary outcome was suturing task time. Secondary outcome parameters were assessment of suturing quality and workload perception. RESULTS: A total of 10 novice participants were included and completed a total of 300 sessions. Median (IQR) suturing time of the first 5 sessions was 231 s (188-291) in the laparoscopic group versus 378 s (282-471) in the FlexDex group versus 189 s (160-247) in the DaVinci Si group. The last 5 sessions showed significant reduction of median suturing time of 143 s (120-190), 232 s (180-265) and 172 s (134-199) respectively. Analysis identified that the learning curve for the laparoscopic needle driver and Da Vinci Si was reached in 5 sessions, compared to 8 sessions for the Flexdex. The laparoscopic needle driver and Da Vinci Si showed a significant shorter median suturing time compared to the FlexDex (p = 0.00). The FlexDex quality assessment scores were significantly lower compared to the laparoscopic (p = 0.00) and robotic (p = 0.00) scores and perceived workload remains high for the FlexDex users. CONCLUSIONS: Ex vivo endoscopic suturing with the FlexDex demonstrated a prolonged learning curve compared to laparoscopic and robotic suturing. The learning curve of the FlexDex is fundamentally different from conventional laparoscopic and robotic instruments. This study provides further insights in the implementation and training of endoscopic suturing techniques.

Encouraging and Detecting Preferential Incipient Slip for Use in Slip Prevention in Robot-Assisted Surgery.

Robotic surgical platforms have helped to improve minimally invasive surgery; however, limitations in their force feedback and force control can result in undesirable tissue trauma or tissue slip events. In this paper, we investigate a sensing method for the early detection of slip events when grasping soft tissues, which would allow surgical robots to take mitigating action to prevent tissue slip and maintain stable grasp control while minimising the applied gripping force, reducing the probability of trauma. The developed sensing concept utilises a curved grasper face to create areas of high and low normal, and thus frictional, force. In the areas of low normal force, there is a higher probability that the grasper face will slip against the tissue. If the grasper face is separated into a series of independent movable islands, then by tracking their displacement it will be possible to identify when the areas of low normal force first start to slip while the remainder of the tissue is still held securely. The system was evaluated through the simulated grasping and retraction of tissue under conditions representative of surgical practice using silicone tissue simulants and porcine liver samples. It was able to successfully detect slip before gross slip occurred with a 100% and 77% success rate for the tissue simulant and porcine liver samples, respectively. This research demonstrates the efficacy of this sensing method and the associated sensor system for detecting the occurrence of tissue slip events during surgical grasping and retraction.

The Value of Surgical Data-Impact on the Future of the Surgical Field.

The combination of computing power, connectivity, and big data has been touted as the future of innovation in many fields, including medicine. There has been a groundswell of companies developing tools for improving patient care utilizing healthcare data, but procedural specialties, like surgery, have lagged behind in benefitting from data-based innovations, given the lack of data that is well structured. While many companies are attempting to innovate in the surgical field, some have encountered difficulties around collecting surgical data, given its complex nature. As there is no standardized way in which to interact with healthcare systems to purchase these data, the authors attempt to characterize the various ways in which surgical data are collected and shared. By surveying and conducting interviews with various surgical technology companies, at least 3 different methods to collect surgical data were identified. From this information, the authors conclude that an attempt to outline best practices should be undertaken that benefits all stakeholders.

[Robotics Helps Usher in a New Era of Neurosurgery].

The application of surgical robots in neurosurgery has formed a rapidly developing and fascinating new field that is revolutionizing the way neurosurgeries are performed. Herein, we discussed the prospects of the future development of neurosurgery robots. We found that, at present, surgical robots are most widely used in stereotactic surgeries in the field of neurosurgery. The use of surgical robots has greatly improved puncturing precision, but it cannot be used in other types of neurosurgeries.With the highly integrated development of imaging technology, mechanical technology, computer control technology, and artificial intelligence, surgical robotics will inevitably witness a surge of rapid development in line with the trend of contemporary needs. Surgical robotics will be applied to more fields of neurosurgery in the future, enhancing surgical safety and efficiency.

A learning robot for cognitive camera control in minimally invasive surgery.

BACKGROUND: We demonstrate the first self-learning, context-sensitive, autonomous camera-guiding robot applicable to minimally invasive surgery. The majority of surgical robots nowadays are telemanipulators without autonomous capabilities. Autonomous systems have been developed for laparoscopic camera guidance, however following simple rules and not adapting their behavior to specific tasks, procedures, or surgeons. METHODS: The herein presented methodology allows different robot kinematics to perceive their environment, interpret it according to a knowledge base and perform context-aware actions. For training, twenty operations were conducted with human camera guidance by a single surgeon. Subsequently, we experimentally evaluated the cognitive robotic camera control. A VIKY EP system and a KUKA LWR 4 robot were trained on data from manual camera guidance after completion of the surgeon's learning curve. Second, only data from VIKY EP were used to train the LWR and finally data from training with the LWR were used to re-train the LWR. RESULTS: The duration of each operation decreased with the robot's increasing experience from 1704 s ± 244 s to 1406 s ± 112 s, and 1197 s. Camera guidance quality (good/neutral/poor) improved from 38.6/53.4/7.9 to 49.4/46.3/4.1% and 56.2/41.0/2.8%. CONCLUSIONS: The cognitive camera robot improved its performance with experience, laying the foundation for a new generation of cognitive surgical robots that adapt to a surgeon's needs.

Investigation of Micro-motion Kinematics of Continuum Robots for Volumetric OCT and OCT-guided Visual Servoing.

Continuum robots (CR) have been recently shown capable of micron-scale motion resolutions. Such motions are achieved through equilibrium modulation using indirect actuation for altering either internal preload forces or changing the cross-sectional stiffness along the length of a continuum robot. Previously reported, but unexplained, turning point behavior is modeled using two approaches. An energy minimization approach is first used to explain the source of this behavior. Subsequently, a kinematic model using internal constraints in multi-backbone CRs is used to replicate this turning point behavior. An approach for modeling the micro-motion differential kinematics is presented using experimental data based on the solution of a system of linear matrix equations. This approach provides a closed-form approximation of the empirical micro-motion kinematics and could be easily used for real-time control. A motivating application of image-based biopsy using 3D optical coherence tomography (OCT) is envisioned and demonstrated in this paper. A system integration for generating OCT volumes by sweeping a custom B-mode OCT probe is presented. Results showing high accuracy in obtaining 3D OCT measurements are shown using a commercial OCT probe. Qualitative results using a miniature probe integrated within the robot are also shown. Finally, closed-loop visual servoing using OCT data is demonstrated for guiding a needle into an agar channel. Results of this paper present what we believe is the first embodiment of a continuum robot capable of micro and macro motion control for 3D OCT imaging. This approach can support the development of new technologies for CRs capable of surgical intervention and micro-motion for ultra-precision tasks.

Automatically steering cardiac catheters in vivo with respiratory motion compensation.

A robotic system for automatically navigating ultrasound (US) imaging catheters can provide real-time intra-cardiac imaging for diagnosis and treatment while reducing the need for clinicians to perform manual catheter steering. Clinical deployment of such a system requires accurate navigation despite the presence of disturbances including cyclical physiological motions (e.g., respiration). In this work, we report results from in vivo trials of automatic target tracking using our system, which is the first to navigate cardiac catheters with respiratory motion compensation. The effects of respiratory disturbances on the US catheter are modeled and then applied to four-degree-of-freedom steering kinematics with predictive filtering. This enables the system to accurately steer the US catheter and aim the US imager at a target despite respiratory motion disturbance. In vivo animal respiratory motion compensation results demonstrate automatic US catheter steering to image a target ablation catheter with 1.05 mm and 1.33° mean absolute error. Robotic US catheter steering with motion compensation can improve cardiac catheterization techniques while reducing clinician effort and X-ray exposure.

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.

Advanced Endoscopic Navigation: Surgical Big Data, Methodology, and Applications.

Interventional endoscopy (e.g., bronchoscopy, colonoscopy, laparoscopy, cystoscopy) is a widely performed procedure that involves either diagnosis of suspicious lesions or guidance for minimally invasive surgery in a variety of organs within the body cavity. Endoscopy may also be used to guide the introduction of certain items (e.g., stents) into the body. Endoscopic navigation systems seek to integrate big data with multimodal information (e.g., computed tomography, magnetic resonance images, endoscopic video sequences, ultrasound images, external trackers) relative to the patient's anatomy, control the movement of medical endoscopes and surgical tools, and guide the surgeon's actions during endoscopic interventions. Nevertheless, it remains challenging to realize the next generation of context-aware navigated endoscopy. This review presents a broad survey of various aspects of endoscopic navigation, particularly with respect to the development of endoscopic navigation techniques. First, we investigate big data with multimodal information involved in endoscopic navigation. Next, we focus on numerous methodologies used for endoscopic navigation. We then review different endoscopic procedures in clinical applications. Finally, we discuss novel techniques and promising directions for the development of endoscopic navigation.

Assessment of the Versius surgical robotic system for dual-field synchronous transanal total mesorectal excision (taTME) in a preclinical model: will tomorrow's surgical robots promise newfound options?

BACKGROUND: The aim of this study was to evaluate the feasibility of the Versius surgical robotic system for transanal total mesorectal excision (taTME) in a preclinical setting. METHODS: Dry laboratory and cadaveric sessions were first conducted for three experienced colorectal surgeons in order to gain familiarity with the modular surgical system and the robotic workstation. After introduction, the system was configured to allow for synchronous, totally robotic taTME in a cadaver. RESULTS: Using the modular robotic system, one surgeon performed the abdominal portion of the operation, including colonic mobilization and vascular pedicle ligation while simultaneously a second surgeon performed the transanal portion of the operation to the point of rendezvous at the peritoneal reflection, where the operation was completed cooperatively. The operation was successfully completed in 195 min demonstrating preclinical feasibility of this unique approach with an emerging robotic system. CONCLUSIONS: This is the first preclinical assessment of the Versius surgical robotic system for taTME. The ability to work simultaneously carries the theoretical advantage of reducing surgical time and thereby reducing overall operative costs. It may also allow surgeons to maintain focus on critical parts of the operation by halving the fatigue associated with long, complex cases such as taTME.

A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery.

Minimally invasive surgery (MIS) techniques are growing in quantity and complexity to cover a wider range of interventions. More specifically, hand-assisted laparoscopic surgery (HALS) involves the use of one surgeon's hand inside the patient whereas the other one manages a single laparoscopic tool. In this scenario, those surgical procedures performed with an additional tool require the aid of an assistant. Furthermore, in the case of a human-robot assistant pairing a fluid communication is mandatory. This human-machine interaction must combine both explicit orders and implicit information from the surgical gestures. In this context, this paper focuses on the development of a hand gesture recognition system for HALS. The recognition is based on a hidden Markov model (HMM) algorithm with an improved automated training step, which can also learn during the online surgical procedure by means of a reinforcement learning process.

Review of emerging surgical robotic technology.

BACKGROUND: The use of laparoscopic and robotic procedures has increased in general surgery. Minimally invasive robotic surgery has made tremendous progress in a relatively short period of time, realizing improvements for both the patient and surgeon. This has led to an increase in the use and development of robotic devices and platforms for general surgery. The purpose of this review is to explore current and emerging surgical robotic technologies in a growing and dynamic environment of research and development. METHODS: This review explores medical and surgical robotic endoscopic surgery and peripheral technologies currently available or in development. The devices discussed here are specific to general surgery, including laparoscopy, colonoscopy, esophagogastroduodenoscopy, and thoracoscopy. Benefits and limitations of each technology were identified and applicable future directions were described. RESULTS: A number of FDA-approved devices and platforms for robotic surgery were reviewed, including the da Vinci Surgical System, Sensei X Robotic Catheter System, FreeHand 1.2, invendoscopy E200 system, Flex® Robotic System, Senhance, ARES, the Single-Port Instrument Delivery Extended Research (SPIDER), and the NeoGuide Colonoscope. Additionally, platforms were reviewed which have not yet obtained FDA approval including MiroSurge, ViaCath System, SPORT™ Surgical System, SurgiBot, Versius Robotic System, Master and Slave Transluminal Endoscopic Robot, Verb Surgical, Miniature In Vivo Robot, and the Einstein Surgical Robot. CONCLUSIONS: The use and demand for robotic medical and surgical platforms is increasing and new technologies are continually being developed. New technologies are increasingly implemented to improve on the capabilities of previously established systems. Future studies are needed to further evaluate the strengths and weaknesses of each robotic surgical device and platform in the operating suite.

Sensor-Based Soft Tissue Balancing in Total Knee Arthroplasty.

Total knee arthroplasty (TKA) is a highly successful procedure with utilization expected to grow substantially over the coming decades. However, the revision burden has not concurrently improved, with over 30% of revisions related to technical imperfections (Mulhall KJ, Ghomrawi HM, Scully S, Callaghan JJ, Saleh KJ, Clin Orthop Relat Res 446:45, 2006; Sharkey PF, Hozack WJ, Rothman RH, Shastri S, Jacoby SM, Clin Orthop Relat Res 404:7, 2002; Wylde V, Hewlett S, Learmonth ID, Dieppe P, Pain 152(3):566, 2011). Accurate alignment and soft tissue balancing have been identified as important factors in mitigating these risks. Historically, accuracy relating to soft tissue balance has relied upon surgeon experience and subjective tactile feel. This chapter will explore the utilization of intraoperative sensors related to soft tissue balancing in total knee arthroplasty.

The role of technology in minimally invasive surgery: state of the art, recent developments and future directions.

The diffusion of minimally invasive surgery has thrived in recent years, providing substantial benefits over traditional techniques for a number of surgical interventions. This rapid growth has been possible due to significant advancements in medical technology, which partly solved some of the technical and clinical challenges associated with minimally invasive techniques. The issues that still limit its widespread adoption for some applications include the limited field of view; reduced manoeuvrability of the tools; lack of haptic feedback; loss of depth perception; extended learning curve; prolonged operative times and higher financial costs. The present review discusses some of the main recent technological advancements that fuelled the uptake of minimally invasive surgery, focussing especially on the areas of imaging, instrumentation, cameras and robotics. The current limitations of state-of-the-art technology are identified and addressed, proposing future research directions necessary to overcome them.

Current applications of robotics in spine surgery: a systematic review of the literature.

OBJECTIVE Surgical robotics has demonstrated utility across the spectrum of surgery. Robotics in spine surgery, however, remains in its infancy. Here, the authors systematically review the evidence behind robotic applications in spinal instrumentation. METHODS This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Relevant studies (through October 2016) that reported the use of robotics in spinal instrumentation were identified from a search of the PubMed database. Data regarding the accuracy of screw placement, surgeon learning curve, radiation exposure, and reasons for robotic failure were extracted. RESULTS Twenty-five studies describing 2 unique robots met inclusion criteria. Of these, 22 studies evaluated accuracy of spinal instrumentation. Although grading of pedicle screw accuracy was variable, the most commonly used method was the Gertzbein and Robbins system of classification. In the studies using the Gertzbein and Robbins system, accuracy (Grades A and B) ranged from 85% to 100%. Ten studies evaluated radiation exposure during the procedure. In studies that detailed fluoroscopy usage, overall fluoroscopy times ranged from 1.3 to 34 seconds per screw. Nine studies examined the learning curve for the surgeon, and 12 studies described causes of robotic failure, which included registration failure, soft-tissue hindrance, and lateral skiving of the drill guide. CONCLUSIONS Robotics in spine surgery is an emerging technology that holds promise for future applications. Surgical accuracy in instrumentation implanted using robotics appears to be high. However, the impact of robotics on radiation exposure is not clear and seems to be dependent on technique and robot type.

Algorithms for Automatically Pointing Ultrasound Imaging Catheters.

A system for automatically pointing ultrasound (US) imaging catheters will enable clinicians to monitor anatomical structures and track instruments during interventional procedures. Off-the-shelf US catheters provide high quality US images from within the patient. While this method of imaging has been proven to be effective for guiding many interventional treatments, significant training is required to overcome the difficulty in manually steering the imager to point at desired structures. Our system uses closed-form four degree of freedom (DOF) kinematic solutions to automatically position the US catheter and point the imager. Algorithms for steering and imager pointing were developed for a range of useful diagnostic and interventional motions. The system was validated on a robotic test bed by steering the catheter within a water environment containing phantom objects. While the system described here was designed for pointing ultrasound catheters, these algorithms are applicable to accurate 4-DOF steering and orientation control of any long thin tendon-driven tool with single or bi-directional bending.

[Tools for laparoscopic skill development - available trainers and simulators]. / A laparoszkópos készségfejlesztés eszközei ­ elérheto trénerek és szimulátorok.

The laparoscopic minimally invasive surgical technique is widely employed on a global scale. However, the efficient and ethical teaching of this technique requires equipment for surgical simulation. These educational devices are present on the market in the form of box trainers and virtual reality simulators, or some combination of those. In this article, we present a systematic overview of commercially available surgical simulators describing the most important features of each product. Our overview elaborates on box trainers and virtual reality simulators, and also touches on surgical robotics simulators, together with operating room workflow simulators, for the sake of completeness. Apart from presenting educational tools, we evaluated the literature of laparoscopic surgical education and simulation, to provide a complete picture of the unfolding trends in this field. Orv Hetil. 2017; 158(40): 1570-1576.

Medical telerobotic systems: current status and future trends.

Teleoperated medical robotic systems allow procedures such as surgeries, treatments, and diagnoses to be conducted across short or long distances while utilizing wired and/or wireless communication networks. This study presents a systematic review of the relevant literature between the years 2004 and 2015, focusing on medical teleoperated robotic systems which have witnessed tremendous growth over the examined period. A thorough insight of telerobotics systems discussing design concepts, enabling technologies (namely robotic manipulation, telecommunications, and vision systems), and potential applications in clinical practice is provided, while existing limitations and future trends are also highlighted. A representative paradigm of the short-distance case is the da Vinci Surgical System which is described in order to highlight relevant issues. The long-distance telerobotics concept is exemplified through a case study on diagnostic ultrasound scanning. Moreover, the present review provides a classification into short- and long-distance telerobotic systems, depending on the distance from which they are operated. Telerobotic systems are further categorized with respect to their application field. For the reviewed systems are also examined their engineering characteristics and the employed robotics technology. The current status of the field, its significance, the potential, as well as the challenges that lie ahead are thoroughly discussed.