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Robotic Surgery
15 Robotic Surgery Pinar Boyraz*,†, Ivo Dobrev‡, Gregory Fischer§, Marko B. Popovic§ *CHALMERS UNIVERSITY O F TECHNOLOGY, GOT HENBURG, SWEDEN † IST ANB UL TE CHNI CAL UNIVERSITY, I STANBUL, TURKEY ‡ UNIVERSITY HOS PITAL ZURICH, UNI VE RSI TY ZURI CH, € Z URIC H, SWI TZ ERL AN D § WO RCES TE R PO LY TEC HNI C I NS TI TUTE , W ORC EST ER, MA, UNI TE D STAT ES
CHAPTER OUTLINE 15.1 Overview of Robotic Surgery ............................................................................................. 431 15.1.1 Introduction: Traditional Robotic Surgery ..............................................................432 15.1.2 Multiarm, Hyperredundant, Continuum, and Soft-Robotic Platforms for Robotic Endoscopy ...................................................................................................434 15.2 Platform-Based Classification of Robotic Surgery ............................................................. 436 15.2.1 Multiarm Robotic Platforms for MIS ........................................................................436 15.2.2 Hyperredundant Robotic Platforms .........................................................................437 15.2.3 Continuum Robots for MIS ......................................................................................437 15.2.4 Soft Robotics for Surgical Applications ...................................................................438 15.2.5 Hybrid Robotic Platforms .........................................................................................440 15.3 Human-Machine Interaction in Robotic Surgery ............................................................... 441 15.4 Autonomy Levels in Robotic Surgery ................................................................................. 442 15.5 Case Studies ......................................................................................................................... 443 15.5.1 Automated Ear Surgeries .........................................................................................443 15.5.2 Reconfigurable and Hyperredundant Robotic Platforms .......................................446 15.6 Conclusion and Future Trends ............................................................................................ 447 References .................................................................................................................................... 447
15.1 Overview of Robotic Surgery Robotic surgery is one of the fastest developing areas within the biomechatronics field, as it provides certain advantages to both surgeons and patients. From the perspective of surgeons the robotic systems may improve both safety and effectiveness of procedure, as well as reduce the physical and cognitive effort thus helping alleviate tiredness, especially in suture-intensive operations. From the perspective of the patients, robotic surgery usually means less postoperative pain, shorter hospital stays and less damage to tissues. According to [1], the first robotic minimally invasive surgery (MIS) was performed in 1987 in the form of laparoscopy. Laparoscopy is a surgical procedure in which a fiber-optic instrument is inserted through the abdominal wall to view the organs in the abdomen or permit small-scale surgery. Since then, the robotic MIS has been accepted in many Biomechatronics. https://doi.org/10.1016/B978-0-12-812939-5.00015-X © 2019 Elsevier Inc. All rights reserved.
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operations involving urology [2], brain and neural system, reproductive system [3], gastronomical, and cardiovascular tracts. Some of these operations do not even need an incision such as natural orifice transluminal endoscopy (NOTE) [4].
15.1.1 Introduction: Traditional Robotic Surgery Surgical robots assist during surgical procedures. They have been used since the mid1980s. Today, the majority of prostatectomies in the United States are robot-aided procedures as chances for successful operation are higher with robotic aid than without. Robotic surgeries are typically minimally invasive. This feature has been around long before the introduction of robots. It is a broad concept that encompasses many common procedures, such as a laparoscopic cholecystectomy, or gall bladder excisions. The procedure refers to a method that avoids long cuts by operating on the body through small (usually 1 cm) entry incisions. Surgeons use long-handled instruments to operate on tissue within the body. Such operations are guided by viewing equipment called endoscopes. These are thin tubes with a camera attached to the end of it that allows the surgeon to view highly magnified real-time three-dimensional images of the operation site on a monitor. The current benefits of robotic surgery include better accuracy, precision, dexterity, tremor corrections, scaled motion, and more recently haptic corrective feedback. These benefits result in more successful surgeries and smaller necessary incision cuts. Overall, the robotic systems have better accuracy and precision than unaided surgeons. Surgical robots are able to position the surgical tools closer to the “right spot” and deviate less from the “right trajectory.” The robot’s end-effectors can be much smaller and more dexterous than a human hand. They can record and filter out a surgeon’s natural hand tremor and rescale movement to increase precision and reduce the chance for error. Lastly, the robot could restrain the surgeon’s movement into undesired directions through haptic feedback. Researchers are formulating new ways to address motion and tissue resistance. For example, the surgical robot could synchronically move with a beating heart such that their relative speed is close to zero. Another possible improvement is the ability for the robot to automatically adapt to the dynamical tissue resistance over time as the sensitivity scale of these processes goes beyond human capabilities. Typically, robotic surgery can be classified as either (i) supervisory-controlled, (ii) telesurgical, or (iii) shared-controlled. The supervisory-controlled approach is the most automated of the three methods. The RoboDoc from Integrated Surgical Systems Inc. is an example of a supervisory-controlled system used in orthopedic surgeries. After the surgeon positions the RoboDoc’s bonemilling tool at the correct position inside the patient, the robot automatically cuts the bone to just the right size for the orthopedic implant. Prior to the surgical procedure, the surgeon needs to prepare the operation through the planning and registration phase. In the planning phase, images of the patient’s body are
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used to determine the right surgical approach. Common imaging methods include computer tomography (CT) scans, magnetic resonance imaging (MRI) scans, ultrasonography, fluoroscopy, and X-ray scans. Next, in the registration phase, the surgeon must locate the points on the patient’s body that correspond to the images created during the planning phase. These points are matched to a 3D model, which can be updated by images seen through cameras or other real-time imaging techniques during surgery. After the robot finds the best fit between the model and reality, the surgical procedure is performed. The tele-surgical approach allows the surgical robot to be tele-operated, that is, operated from a distance by a human surgeon. In practice, the robot and the surgeon are only a couple of meters apart. Tele-operation is also possible across larger distances. However, problems such as time delays (i.e., tele-surgical latencies) and the available bandwidth (i.e., the amount of information that can be transferred per unit time) need to be considered. The tele-surgical approach is used by the da Vinci Surgical System, which was invented by Philip S. Green and developed by Intuitive Surgical Inc. This system currently dominates the surgical robot market. Initially dubbed Mona (after Leonardo’s Mona Lisa), the system was rechristened the da Vinci Surgical Robot in 1999; according to Mr. Green “…in honour of the man who had invented the first robot.” Although da Vinci never invented or built a real robot (credit for that goes to Tesla), he made many drawings of various mechanisms. The da Vinci System consists of three primary components: (1) a viewing and control console that is used by surgeon, (2) a vision cart that holds the endoscopes and provides visual feedback and (3) a surgical robot’s manipulator arm unit that includes three or four arms, depending on the model. The instruments that are attached to the arms are highly specialized. Functions for them include clamping, cutting, suturing, tissue manipulation, cauterizing, etc. It takes some time for surgeons to get accustomed to the da Vinci System. According to a study, even with initial training program, provided by the Intuitive Surgical, it takes about 12–18 operations before surgeons feel comfortable performing the procedure. Often, during this period, surgeons complain on lack of tactile force feedback or ability to “feel” the tissue. The shared-controlled approach refers to the method by which the robot is not just motion tele-operated as it can decide to resist the surgeons’ intended movement if it deems that it would not be beneficial. Typically, the work space is split into several segments and the system behaves differently based on different localization according to safe, close, boundary, or forbidden classification. For example, if surgeon moves a cutting tool in the direction of tissue that should not be damaged, the robot will apply the force haptic feedback that will grow stronger as the cutting tool comes closer to the fragile tissue. In other words, here, surgeon again “feels” the virtual representation of tissue that may have preprogrammed specifications different from the real tissue as well as somewhat different localization in space.
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15.1.2 Multiarm, Hyperredundant, Continuum, and Soft-Robotic Platforms for Robotic Endoscopy Although the first widely used and FDA approved robotic platforms for surgery were based on industrial six degrees of freedom (DOF) serial and rigid robotic manipulator such as [5], the robotic platforms are currently often designed with more DoF and with some level of flexibility. The hyperredundant robots with more DoF and dexterity are proposed to address difficult passages. Theoretically, a continuum robotic platform has infinite number of DoF and hence it is anticipated to be able to improve surgical procedures still further. Besides, the tubular/telescopic continuum robotic platforms can be miniaturized easily due to their simple mechanic construction. Further improvement to surgical platforms can be obtained by employing the inherent compliance of the soft materials. This chapter addresses above mentioned aspects and reviews some of multiarm, hyperredundant, continuum, and soft-robotic platform examples from literature and case studies from selected research laboratories. The forerunners of robotics surgical systems are endoscopic platforms since the inception of this field. An endoscopic process typically involves a small incision through which the rigid or flexible endoscopic devices is inserted to provided view on the tissue that is being operated. Because the insertion point/trocar limits the movement of the robotic arm in two directions, see for example Ref. [6], the remaining DOF for the endoscopic robotic platforms are totaled to four DOF (see Fig. 15.1). Although this usually limits the dexterity and manipulation of the end effector, endoscopic robots are still advantageous because they cause less pain, have a better cosmetic look after the operation, and the cost is much lower. In Ref. [6], a comprehensive classification of endoscopes is given including the categories of laparoscopes with or without camera, the manipulator size, and if the sterilization is possible.
FIG. 15.1 Reduced DOF for endoscopic tool after insertion [6].
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FIG. 15.2 (A) Overview of MASTER system and (B) structure of the slave manipulator. Original illustration by P. Boyraz.
A consensus by European Association of Endoscopic Surgeons (EAES) was reached in 2014 [7] defining the types of operations that can be performed using robotic endoscopy and the related requirements for safe and efficient execution. Ref. [8] summarizes robotic flexible endoscopy platforms for diagnosis and treatment of gastrointestinal diseases according to articles accessible through PubMed published between 2010 and 2015. According to that review Neoguide (Intuitive Surgical, United States) is FDA approved while commercially available robotic flexible endoscopic platforms include: Invendoscope (Invendo Medical Gmbh, Germany), Aer-O-scope (GI View Ltd, Israel), Endotics (ERA Endoscopy SRL, Italy), Endomina (Endo Tools Therapeutics, Belgium), and Viacath (Hansen Medical, United States). The other notable system mentioned in this review is MASTER (EndoMASTER Pte, Singapore) system, presented in Ref. [9] in adequate detail (see Fig. 15.2). This robotic system has a master and a slave manipulator driven by tendon-sheath actuation. The system also supports force-feedback for the surgeon. Clinical study involving 42 patients that undertook endonasal trans-sphenoidal surgery has been reported in Ref. [10]. There, a rigid endoscope is used with iArmS robotic platform as a support robot. More advanced applications of robots in endoscopy involve flexible robotic platforms [11] and endoscopic capsules (ECs) [12]. As discussed in Ref. [11], the ideal robotic endoscope has not been realized yet as there are numerous challenges that need to be overcome especially for flexible endoscopes. These challenges are mainly concerning the use of the robots for manipulation of the endoscopes themselves for the remote insertion and incorporation of such robots not only for NOTE type of operations but also for endoscopic submucosal dissection (ESD). The setup for flexible endoscopic application development is shown in Fig. 15.3. As a frontier in robotic endoscopy, the ECs [12] can open a new solution window to the problems with tethered and rigid systems. The first applications of EC were aimed at the drug delivery and diagnosis; however, recently they are being developed for the operational purposes. The operative capabilities of ECs are still under development and the movement of the device is usually provided by an external magnet.
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FIG. 15.3 The setup for flexible endoscopic application development [11]. Original illustration by P. Boyraz.
15.2 Platform-Based Classification of Robotic Surgery In this section, the robotic platforms used as autonomous, semiautonomous or assistive systems in the operations are classified based on the structure. The robotics platforms may increase the number of DoF either by addition of robotic arms to form multiarm structure, discussed in Section 15.2.1, or by having hyperredundant backbones, discussed in Section 15.2.2. In terms of minimizing the dimensions and having almost limitless DOF, the continuum robotics is considered in Section 15.2.3. Recent research focused on soft robotics in the context of robotics surgery is addressed in Section 15.2.4. Several examples of hybrid systems that may eventually lead to general robotic platform benefiting from increased DoF, compact structure and inherent compliance altogether are reviewed in Section 15.2.5.
15.2.1 Multiarm Robotic Platforms for MIS Over the last several decades there was a steady progress that finally led to sophistication of current gold standard in robotics surgery field in the form of the da Vinci Surgical System (Intuitive Surgical, Sunnyvale, CA, USA); detailed overview of these early historical developments is provided in Ref. [13]. In fact, the surgeons in the operation room need assistance from the other surgeons or staff nurse to hold some of the gripper carrying manipulators, endo-luminal devices or guidance catheters while they operate on the tissue with minimal stress and maximum safety. Therefore, the obvious and very first use of the robotics in the surgery has been the adaptations of the robots as third arm [14] or use multiple-arms of robotic platforms for dexterous manipulation [15]. There are even some cases in which the multiarm robot is used for a very specific surgical operation requiring three dimensional (3D) navigation
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and involving bone grafting [16]. Although being beneficial and safer, the multiarm robotic platforms have some disadvantages considering the need and cost of the optimization for the configuration space according to the patient’s body and the operable area [15]. Because of such disadvantages and costly installation/optimization process, other alternatives such as hyperredundant robot-arms and continuum robotic platforms are proposed. These two specific design ideas will be detailed in the next sections.
15.2.2 Hyperredundant Robotic Platforms Robotic platforms of the hyperredundant or piece-wise continuum design mostly use rigid or semirigid backbones. Recently proposed hyperredundant modular structures can be found in Refs. [17–19]. In Ref. [17], high dexterity and high-stiffness requirements for actual operation are provided although the design has limited compliance. The design in Ref. [17] also has intricate mechanical structure which can be difficult to miniaturize for medical applications required to work in limited operation space. More advanced prototypes can have control over the stiffness [18], however, they may have poorer modulebased controllability. Even though it is possible to have applications with better control [19] featuring continuum elastic backbone while segmenting the structure into modules with coupling plates, the compactness cannot be guaranteed. Most hyperredundant platforms have cable driven structures because they are lightweight and compact. However, there is an inherent limitation of such mechanisms due to cable friction and interdependency between the sections of the modules. Early examples of hyper-redundant manipulators with full solution on kinematics and dynamics are presented in Refs. [20–22]. Although the kinematics and dynamics are widely studied, the relevant control algorithms suggested for such mechanisms are not mature. For example, a modular control scheme is proposed in Ref. [23] with some promising results, however, more research efforts are needed in control aspect of hyperredundant manipulators. In that respect, the work in Ref. [24] presents a hybrid motion/force control application. Although the actual algorithm is developed for multibackbone continuum robots, it can be modified for hyperredundant robotic platforms using simplified kinematics. What is more exciting in hyperredundant platforms’ research is that very recent developments are taking place providing controllable stiffness in robotic arms. In Ref. [25], the researchers proposed such a platform to be used in laparo-endoscopic single-site surgery. The structure can be switched between five DOF rigid status to seven DOF compliant status according to the task required in the operation (see Fig. 15.4).
15.2.3 Continuum Robots for MIS A comprehensive survey on the continuum robots for medical applications [26] can guide the reader on which type of surgical interventions these type of robots should be preferred. A continuum robot has infinite DOF and can be driven by cables, hydraulic actuation or shape-memory-alloys based on the application and the level of required miniaturization.
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FIG. 15.4 The hyperredundant robotic arm with an adjustable section employing PCM alloy for the stiffness control via temperature change. Original illustration by P. Boyraz prepared based on J. Wang, S. Wang, J. Li, X. Ren, R.M. Briggs, Development of a novel robotic platform with controllable stiffness manipulation arms for laparoendoscopic single-site surgery (LESS), J. Med. Robot. Comput. Assist. Surg. 14 (2018) 1–16.
In Ref. [27] a co-centric tube type of robot is proposed using piezoelectric actuation. The co-centric tube type of continuum robots needs to be precurved according to their task and workspace in the operation. This might turn to be a disadvantage if the same medical device is desired to be used on different patients requiring different operational workspace. In addition, this type of continuum platforms may have limited capabilities of translational motion. A novel continuum manipulator design using serially connected double-layer planar springs [28] overcome these disadvantages to some degree (see Fig. 15.5). In addition, the proposed structure behaves like a helical spring, but its contraction and bending motion are decoupled, therefore easier to control.
15.2.4 Soft Robotics for Surgical Applications Soft-material robotic platforms open up a new path for obtaining compliant and safe platforms. A good example of such an application can be seen in Ref. [29]. In this work, the researchers used flexible fluidic actuators allowing dexterous and safe navigation. It was possible to overcome the restrictions that are normally posed in a situation where the rigid manipulator has to work in a cavity with multiple organs in close proximity. Fig. 15.6 depicts the advantage of the soft robot in terms of dexterity in a confined region.
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FIG. 15.5 A novel continuum robotic platform with multilayer deformable springs. Original illustration by P. Boyraz prepared based on P. Qi, C. Qui, H. Liu, J.S. Dai L.D. Seneviratne, K. Althoefer, A novel continuum manipulator design using serially connected double-layer planar springs, IEEE/ASME Trans. Mechatr. 21(3) (2016) 1281–1292.
FIG. 15.6 An illustration of dexterous advantage of the soft robot compared to rigid robot. Original illustration by P. Boyraz prepared based on H. Abidi, G. Gerboni, M. Brancadoro, J. Fras, A. Diodato, M. Cianchetti, H. Wurdemann, K. Althoefer, Highly dexterous 2-module soft robot for intra-organ navigation in minimally invasive surgery, Int. J. Med. Robot. Comput. Assist. Surg. 14 (2018) 1–9.
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Another work can be taken as a guiding example for planning the navigation or locomotion of such robots in tubular environments [30]. Although the application is generic, it can be easily modified for cardiovascular or urological interventions because it prevents full occlusion of the tubular channel while navigating in it. This is a big advantage compared to traditional rigid structures as they tend to block such channels and in extreme cases cause tissue damage.
15.2.5 Hybrid Robotic Platforms The hybrid robotic platforms strive to combine the best properties of serial rigid robotic arms with continuum and/or soft robots to achieve superior qualities such as position accuracy and compliancy at the same time. For example, the system described in Ref. [31] comprises of a serial manipulator which is connected to a continuum platform. In this combined hybrid structure the robot was observed to have superb positioning and tracking accuracy. A conceptual design of the hybrid robotic platform can be seen in Fig. 15.7. Normally, when entering into human body through the incision, two DOF provided by the rigid arm are sacrificed. However, in this setup it can be regained, thanks to the flexible continuum robot at the end. Herein, the word “hybrid” can also refer to the combination of serial and parallel links (i.e., open and closed kinematic chains) to form a better spatial capability for the end effector [32]. Another possibility of obtaining a hybrid platform is to combine the continuum structures with soft materials, as seen in Ref. [33], incorporating also reconfigurability. This hybrid platform (see Fig. 15.8), although not used in medical robotics yet could be easily adapted to many surgical applications, provided that it can be manufactured in smaller dimensions.
FIG. 15.7 Hybrid robotic system combining a flexible continuum robot and a rigid 6 DOF robotic arm [31]. Original illustration by P. Boyraz.
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FIG. 15.8 Soft compliant manipulator with continuum segments, SIMBA [26]. Original illustration by P. Boyraz.
15.3 Human-Machine Interaction in Robotic Surgery One of the grand challenges of the robotic surgery nowadays is in the area of designing efficient and ergonomic human-machine interaction (HMI) systems to improve the augmentation of the surgeon and the robot. Considering that not all the surgical platforms could be fully autonomous, HMI systems will always be needed in the operation rooms to facilitate the integration of robotic tools for surgery. A reasonable starting point of such technology involves the virtual-reality applications [34] to simulate the high-skill tasks for surgeons such as suturing. A more direct application of HMI systems could be teleoperated surgical systems. A recent and exciting example of such a system uses a haptic interface to manipulate and steer miniaturized untethered soft-magnetic grippers in Ref. [35]. In addition to new HMI system designs in robotic surgery, observing the human factors and ergonomics criteria is also very important. For example, in Ref. [36], human arm stiffness is examined during the virtual tele-operation of robotic manipulators. In that study, the researchers have proposed a nondisruptive method to study the stiffness of the human arm during different tasks within an operation. This type of performance analysis is required and must be performed to assess the stability and precision of the execution of the task, because the overall system is a combination of the human skills incorporated with the robotic system’s dynamics. The collaborative robots could be considered as being on the very top of HMI research in the robotic surgery field. These systems are aimed at providing the surgeon more stable assistance, especially in effort-laden suture procedures. An example of such a system is detailed in Ref. [37]. This type of system must have the capability to recognize surgical gestures made by surgeon and should have an algorithm supporting the autonomous decision-making. The experimental setup for the proposed collaborative system is presented in Fig. 15.9.
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FIG. 15.9 Experimental setup for development of collaborative robot platform. Original illustration by P. Boyraz prepared based on E. Bauzano, B. Estebanez, I. Garcia-Morales, V. Munoz, Collaborative human-robot system for HALS suture procedures, IEEE Syst. J. 10(3) (2016) 957–966.
15.4 Autonomy Levels in Robotic Surgery As with any system that is gradually evolving into autonomous operation modes, the surgical robots are also under development to make that transition in a safe manner. As it is also realized on time by the authorities, a new ISO standard has been compiled defining the autonomy levels in medical equipment [38]. In addition to standardization efforts by experts and authorities, the research community is also responding via well-funded research projects such as I-SUR (EU FP7 funded, Intelligent Surgical Robotics). In this project, the researchers developed innovative solutions [39] such as surgical planning and execution of movement of robot arms in contact with a deformable environment, an interface minimizing the cognitive load of the surgeon through supervision of the actions and intraoperative sensing together with reasoning to detect the transitions between the autonomous and tele-operated modes. In fact, in Ref. [40] this transition is detailed using a two-layered bilateral control, stabilizing the process of authority transition from robot to surgeon. More focused studies also exist, for example, integrating human surgeon in an automated suturing task as seen in Ref. [41]. In that study, the researchers were able to accelerate the suturing process by 79% using one-master and two-slave system with force sensing. The autonomous suturing process can be seen in Fig. 15.10.
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FIG. 15.10 Human-integrated autonomous suturing process. Original illustration by P. Boyraz prepared based on K. Watanabe, T. Kanno, K. Ito, K. Kawashima, Human-integrated automation of suturing task with one-master two-slave system for laparoscopic surgery, IEEE Int. Conf. on Advanced Intelligent Mechatronics (AIM), Banf, Alberta, Canada, 2016.
In order to execute a semiautonomous surgical process, task recognition is necessary for the surgical robot. In Ref. [42], a distance-based time series classification is used for task recognition. The recognition output is used to adjust the position of the camera upon recognizing the surgeon’s movements in terms of kinematic time series. Using the (dis) similarity measures between the tasks, the robot is able to distinguish for example, the task of suturing from needle passing or knot tying movements.
15.5 Case Studies 15.5.1 Automated Ear Surgeries Surgical manipulations of the ear, such as ones for implantable hearing aids, are able to help patients with hearing deficiencies. However, such operations require access to the middle and/or inner ear, which involves drilling a cavity into the mastoid (mastoidectomy), the skull bone behind the ear. Such manual procedures produce openings physically much larger (several centimeters) than optimally required for the insertion of the implantable hearing aid (a few millimeters), and this is done primarily to obtain visual access to underlaying key landmark features, used to help locate the target location, while navigating away from critical anatomical structures that should not be harmed. Even if the
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incision opening would be much smaller, the tool trajectory still needs to pass through a window of a few millimeters, where all critical biological structures and tissues are located. Thus, a precision smaller than 0.5 mm is needed for planning, navigation, guidance during operation. There are several existing solutions to this challenge that have been applied in clinical and in vitro conditions, however all share common crucial procedural steps. Below is a brief overview of some of the existing solutions with emphasis on the common as well as unique parts of their methodology. One solution to this problem [43] is based on the concept of a stereotactic frame, custom build for each individual operation and patient, which aids the guidance of the drilling instrument during the surgical procedure, in order to precisely reach the target location while avoiding crucial anatomical structures. The procedure consists of five major steps. The procedure starts with attachment of fiducial markers, in the form of bone anchored percutaneous screws, to the patient’s head, surrounding the mastoid (the surgical access area). The design of the screws is such that they are clearly visible in the X-ray domain, and have a well-defined point of contact, accessible for physical contact with a registration tool. During the second step, the patient’s head is preoperatively scanned using a medical X-ray computed tomography (CT) scanner, with a voxel size of approximately 0.3 mm, depending on the scan conditions. In the third step, the volumetric scan data is then analyzed, crucial anatomical features and structures are identified, and the geometry of the anchor screws is registered relative to their CAD model. Based on all these features, a preoperative planning is made, where the drilling trajectory, defined by the target (final) and entry locations, for the surgical procedure is established such that the anatomical structures, including the facial nerve and major blood vessels, are safely avoided. The anatomical feature segmentation and identification as well as the trajectory planning, is performed automatically in a matter of minutes, and the resulting trajectory is verified by a surgeon [44]. In the fourth step, custom stereotactic frame is manufactured such that it provides attachment points for custom legs, which anchor the frame to the screws in the skull. The stereotactic frame also features a channel to guide a medical drill along the preoperatively defined surgical entry trajectory, virtually defined in the previous step. The frame could be manufactured through means of rapid prototyping [45], which, while appealing for its ease of use, proved to be time consuming (48-h lead time) as it doubles or triples the total procedural time. This delay has been overcome, by modifying the design of the stereotactic frame to allow it to be manufactured by more traditional manufacturing techniques (e.g., via a CNC milling machine) on site, which decreases the leadtime down to a few minutes. In the final step, the stereotactic frame is attached to the anchor screws at the patient’s head. Once the frame is firmly secured, the drilling can commence. Tests so far indicate drill jitter of approximately 70 μm on average, with target and trajectory accuracies in the order of 0.4 mm, verified in vitro. Total time for steps 2–4, which are at the core of the automated surgical process, is approximately 30 min. During the drilling process, a typical drill size of 1 mm diameter is used, which leaves <1 mm (sometimes <0.5 mm) of clearance from crucial anatomical structures to be avoided, as
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FIG. 15.11 Overview of a virtual trajectory definition with tolerance and minimal distances to crucial anatomical structures to be avoided during the drilling procedure. Original illustration by P. Boyraz prepared based on N. Gerber, B. Bell, K. Gavaghan, C. Weisstanner, M. Caversaccio, S. Weber, Surgical planning tool for robotically assisted hearing aid implantation, Int. J. Comput. Assist. Radiol. Surg. 9(1) (2014) 11–20.
shown in Fig. 15.11. The generality of such a procedure allows its application to a great variety of surgical procedures in the head, where the skull provides solid points for anchoring of the stereotactic frame. While accurate, the above-mentioned approach to registration, between the physical space (patient and surgical tool) and virtual planning (CT scan data and trajectory), relies on semi-manual manipulation (assembly and adjustment of the stereotactic frame), which leaves room for an accidental error. This has been further improved in the approaches of two other independent research groups [46, 47], where the physical stereotactic frame has been substituted with an optical [46] or electromagnetic [40] tracking system, which provides precise (below 100 μm) location of the tool relative to the patient, via bone anchored fiducial screws. In addition, five or six DOF serial robotic manipulator is incorporated into the overall procedure to provide accurate and consistent way of holding and moving the surgical drilling tool intraoperatively. The combination of a robotic manipulator and an automatic guidance system allows for a fully automated execution of the registration with the patient’s head and drilling via a predefined trajectory. In addition, one of the systems [47] includes a load cell at the tool holder interface to provide information on the exerted manipulation forces, which allows tele-operated haptic control mode, during which a surgeon guides the robot via a force-feedback controller. While such mode of operation seems to add additional complexity to the overall setup and procedure, it is a crucial feature for the adoption of such technologies, allowing further development and optimization.
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15.5.2 Reconfigurable and Hyperredundant Robotic Platforms In this part, the design of hyperredundant and modular robotic structures is detailed by emphasizing their features such as independent module/segment controllability and variable-adjustable stiffness. The proposed designs [48] are aimed at improving both position and force control of such structures employing whole-body shape control and local stiffness control in the robotic catheter on module basis. Three different module designs for hyperredundant mechanisms are depicted in Fig. 15.12. The first mechanism is called ‘hybrid’ comprising a universal joint placed in between two parallel plates. This mechanism has three DOF per module, having pan and tilt for adjusting the heading angle while using the translational movement to shrink or elongate while adjusting its stiffness. The helical spring around the middle shaft provides inherent compliance for the module. The second mechanism is 3 SPS having spherical-prismatic-spherical joints in each strut can be considered as a reconfigurable parallel mechanism. It provides stiffness adjustments by relocating the connection points of the struts on the lower plate. The struts can also elongate and contract along their axis so that the hyperredundant platform can be adjusted when passing along difficult cavities. Finally, the last module is named after the seahorse tail since it is inspired by the cross section of the biological structure. This mechanism can radially change dimensions in a similar manner of seahorse tail structure, using the oblique muscles. The modules are connected by a spherical joint in the middle. Since the radial struts are spring-loaded, therefore, the radial stiffness can be adjusted. The main advantage of reconfigurable hyperredundant mechanisms is that each segment can be controlled separately, and the multidegree-of-freedom makes it possible to control the whole-body shape of the manipulator to reduce the risk of harming the tissues during the navigation task. If the modules also have variable stiffness or reconfigurability as it is shown here, the versatility and the safety of the hyperredundant platforms increase. Since robotic platforms should accomplish tasks such as navigation, diagnosis, and operation they may have to support different levels of stiffness.
FIG. 15.12 Modules for hyperredundant backbone construction, from left to right: Hybrid-module, radially reconfigurable 3 SPS parallel-kinematic mechanism, and seahorse tail section [48].
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15.6 Conclusion and Future Trends Robotic surgery has reached a certain maturity level in terms of application-specific solutions using multiple-arm robots and employing master-slave systems. However, several ongoing research directions involving for example soft-robotics, human-robot collaboration, and the transition to higher levels of autonomy, hold a promise to still further advance this field. Another trend for surgical robotics include micro-robots that could be delivered in gastrointestinal or cardiovascular tract to perform certain surgical operations, however, up to date research has only achieved a mesoscale prototype that could both navigate in torturous channels and perform an operation, which may require certain force levels. In summary, the field of surgical robotics is still an active area of research with the aim of obtaining minimal invasiveness while achieving autonomous navigation and operation. The rapidly developing field of robotic surgery will also cause the rethinking of the role of surgeons in the operation room. While surgical robots could help in achieving more reliable, faster and standardized procedures, they will be still controlled (in fully manual or semiautonomous mode) by the surgeons, who will need to expand their field of expertise and knowledge, to use more efficiently the capabilities of such robotic systems. Surgeon will be still a key figure in the operating theater; however, surgeon’s role will expand into augmenting existing surgical procedures or even designing completely new ones utilizing emerging novel systems. As the range of capabilities of surgical robotics expands, so will grow the importance of experienced surgeons to adopt new technologies and further advance the efficiency and success rate of surgical procedures.
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[9] S.J. Phee, A.P. Kencana, V.A. Huynh, Z.L. Sun, S.C. Low, K. Yang, D. Lomanto, K.Y. Ho, Design of a master and slave transluminal endoscopic robot for natural orifice transluminal endoscopic surgery, Proc. IMechE Part C: J. Mech. Eng. Sci. 224 (2010) 1495–1503. [10] T. Ogiwara, T. Goto, A. Nagm, K. Hongo, Endoscopic endonasal transsphenoidal surgery using the iArmS operation support robot: initial experience in 42 patients, Neurosurg. Focus. 42 (5) (2017) 1–5. E10. [11] K. Kume, Flexible robotic endoscopy: current and original devices, Comput. Assist. Surg. 21 (1) (2016) 150–159. [12] P.R. Slawinski, K.L. Obstein, P. Valdastri, Emerging issues and future developments in capsule endoscopy, Tech. Gastrointest. Endosc. 17 (2015) 40–46. [13] M.E. Moran, Evolution of robotic arms, J. Robot. Surg. 1 (2007) 103–111. [14] E. Abdi, M. Bouri, S. Himidan, E. Burdet, H. Bleuler, Third arm manipulation for surgical applications: an experimental study, in: New Trends in Medical and Service Robots, 2016, pp. 153–163. [15] Z. Li, D. Milutinovic, J. Rosen, Design of a multi-arm surgical robotic system for dexterous manipulation, J. Mech. Robot. 8 (061017) (2016) 10. [16] H. Zhao, J. Tian, D. Li, C. Ai, Design of a multi-arm robot for mandible reconstruction surgery, Appl. Mech. Mater. 654 (2014) 187–190. [17] O. Salomon, A. Wolf, Inclined links hyper-redundant elephant-trunk-like robot, J. Mech. Robot. 4 (2012). 6 pp. [18] Z. Li, H. Ren, P.W.Y. Chiu, R. Du, H. Yu, A novel constrained wire-driven flexible mechanism and its kinematic analysis, Mech. Mach. Theory 95 (2016) 59–75. [19] M.M. Tonapi, I.S. Godage, A.M. Vijaykumar, I.D. Walker, A novel continuum robotic cable aimed at applications in space, Adv. Robot. 29 (6) (2015) 861–875. [20] G.S. Chirikjian, J.W. Burdick, A modal approach to hyper-redundant manipulator kinematics, IEEE Trans. Robot. Autom. 10 (3) (1994) 343–354. [21] G.S. Chrikjian, J.W. Burdick, Kinematically optimal hyper-redundant manipulator configurations, IEEE Trans. Robot. Autom. 11 (6) (1995) 794–806. [22] G.S. Chrikjian, Hyper-redundant manipulator dynamics: a continuum approximation, Adv. Robot. 9 (3) (1994) 217–243. [23] N.C. Cho, H. Jung, J. Son, K.G. Kim, A modular control scheme for hyper-redundant robots, Int. J. Adv. Robot. Syst. 12 (2015) 91. [24] A. Bajo, N. Simaan, Hybrid motion/force control of multi-backbone continuum robots, Int. J. Robot. Res. 35 (4) (2016) 422–434. [25] J. Wang, S. Wang, J. Li, X. Ren, R.M. Briggs, Development of a novel robotic platform with controllable stiffness manipulation arms for laparoendoscopic single-site surgery (LESS), J. Med. Robot. Comput. Assist. Surg. 14 (2018) 1–16. [26] J. Burgner-Kahrs, C. Rucker, H. Choset, Continuum robots for medical applications: a survey, IEEE Trans. Robot. 31 (6) (2015). [27] H. Su, G. Li, D.C. Rucker, R.J. Webster III, G. Fischer, A. Concentric Tube, Continuum robot with piezoelectric actuation for MRI-guided closed-loop targeting, Ann. Biomed. Eng. 44 (10) (2016) 2863–2873. [28] P. Qi, C. Qui, H. Liu, J.S. Dai, L.D. Seneviratne, K. Althoefer, A novel continuum manipulator design using serially connected double-layer planar springs, IEEE/ASME Trans. Mechatr. 21 (3) (2016) 1281–1292. [29] H. Abidi, G. Gerboni, M. Brancadoro, J. Fras, A. Diodato, M. Cianchetti, H. Wurdemann, K. Althoefer, Highly dexterous 2-module soft robot for intra-organ navigation in minimally invasive surgery‘, Int. J. Med. Robot. Comput. Assist. Surg. 14 (2018) 1–9.
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[30] M.D. Gilbertson, G. McDonald, G. Korinek, J.D. Van de Ven, T.M. Kowalewski, Serially actuated locomotion for soft robots in tube-like environments, IEEE Robot. Autom. Lett. 2 (2) (2017) 1140–1147. [31] G. Smoljkic, G. Borghesan, A. Devreker, A.V. Poorten, B. Rosa, H. De Praetere, J. De Schutter, D. Reynaerts, J.V. Sloten, Controlof a hybrid robotic system for computer-assisted interventions in dynamic environments, Int. J. CARS 11 (2016) 1371–1383. [32] A. Singh, E. Singla, S. Soni, A. Singla, Kinematic modeling of a 7-degree of freedom spatial hybrid manipulator for medical surgery, Proc. IMechE Part H: J. Eng. Med. 232 (1) (2018) 12–23. [33] A.K. Mishra, E. Del Dottore, A. Sadeghi, A. Mondini, B. Mazzolai, SIMBA: tendon-driven modular continuum arm with soft reconfigurable gripper, Front. Robot. AI 4 (4) (2017) 1–10. [34] D.J. Kiely, W.H. Gotlieb, S. Lau, X. Zeng, V. Samouelian, A.V. Ramanakumar, et al., Virtual reality robotic surgery simulation curriculum to teach robotic suturing: a randomized controlled trial, J. Robot. Surg. 9 (2015) 179–186. [35] C. Pacchierotti, F. Ongaro, F. Van den Brink, C. Yoon, D. Prattichizzo, et al., Steering and control of miniaturized untethered soft magnetic grippers with haptic assistance, IEEE Trans. Autom. Sci. Eng. Inst. Electr. Electron. Eng. 15 (1) (2018) 290–306. [36] J. Buzzi, G. Ferrigno, J.M. Jansma, E. De Momi, On the value of estimating human arm stiffness during virtual teleoperation with robotic manipulators, Front. Neurosci. 11 (2017), 528. [37] E. Bauzano, B. Estebanez, I. Garcia-Morales, V. Munoz, Collaborative human-robot system for HALS suture procedures, IEEE Syst. J. 10 (3) (2016) 957–966. [38] ISO Standard, IEC/TR 60601-4-1:2017, Medical Electrical Equipment- Part 4-1: Guidance and Interpretation-Medical Electrical Equipment and Medical Electrical Systems Employing a Degree of Autonomy. [39] R. Muradore, P. Fiorini, G. Akgun, D.E. Barkana, M. Bonfe, F. Boriero, A. Caprara, et al., Development of a cognitive robotic system for simple surgical tasks, Int. J. Adv. Robot. Syst. 12 (37) (2015) 1–20. [40] F. Ferraguti, N. Preda, A. Manurung, M. Bonfe, O. Lambercy, R. Gassert, et al., En energy tank-based interactive control architecture for autonomous and teleoperated robotic surgery, IEEE Trans. Robot. 31 (5) (2015) 1073–1088. [41] K. Watanabe, T. Kanno, K. Ito, K. Kawashima, Human-integrated automation of suturing task with one-master two-slave system for laparoscopic surgery, in: IEEE Int Conf. on Advanced Intelligent Mechatronics (AIM), Banf, Alberta, Canada, 2016. [42] M. Fard, A.K. Pandya, R.B. Chinnam, M.D. Klein, R.D. Ellis, Distance-based time series classification approach for task recognition with application in surgical robot autonomy, Int. J. Med. Robot. Comput. Assist. Surg. 13 (e1766) (2017) 1–9. [43] R.F. Labadie, R. Balachandran, J. Mitchell, J.H. Noble, O. Majdani, D. Haynes, M. Bennett, B.M. Dawant, J.M. Fitzpatrick, Clinical validation study of percutaneous cochlear access using patient customized micro-stereotactic frames, Otol. Neurotol.: Off. Publ. Am. Otol. Soc. Am. Neurotol. Soc. Eur. Acad. Otol. Neurotol. 31 (1) (2010) 94. [44] J.H. Noble, F.M. Warren, R.F. Labadie, B.M. Dawant, J.M. Fitzpatrick, Determination of drill paths for percutaneous cochlear access accounting for target positioning error, Proc. SPIE 6509 (2007) 650925.1–650925.10. [45] R.F. Labadie, J.H. Noble, B.M. Dawant, O. Majdani, R. Balachandran, J.M. Fitzpatrick, Clinical validation of percutaneous cochlear implant surgery: initial report, Laryngoscope 118 (2008) 1031–1039. 18401279. [46] N. Gerber, B. Bell, K. Gavaghan, C. Weisstanner, M. Caversaccio, S. Weber, Surgical planning tool for robotically assisted hearing aid implantation, Int. J. Comput. Assist. Radiol. Surg. 9 (1) (2014) 11–20.
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[47] R. Torres, G. Kazmitcheff, D. De Seta, E. Ferrary, O. Sterkers, Y. Nguyen, Improvement of the insertion axis for cochlear implantation with a robot-based system, Eur. Arch. Otorhinolaryngol. 274 (2) (2017) 715–721. [48] P.R. Nasdar, P. Boyraz, T. Ortmaier, A. Raatz, Development of compliant hyper-redundant mechanisms for robotic catheters and analysis of controllability, Deutche Gesselschaft fuer Robotik (DGR) Days (2016) 29–30 Leipzig, Germany.
CHAPTER OUTLINE 15.1 Overview of Robotic Surgery ............................................................................................. 431 15.1.1 Introduction: Traditional Robotic Surgery ..............................................................432 15.1.2 Multiarm, Hyperredundant, Continuum, and Soft-Robotic Platforms for Robotic Endoscopy ...................................................................................................434 15.2 Platform-Based Classification of Robotic Surgery ............................................................. 436 15.2.1 Multiarm Robotic Platforms for MIS ........................................................................436 15.2.2 Hyperredundant Robotic Platforms .........................................................................437 15.2.3 Continuum Robots for MIS ......................................................................................437 15.2.4 Soft Robotics for Surgical Applications ...................................................................438 15.2.5 Hybrid Robotic Platforms .........................................................................................440 15.3 Human-Machine Interaction in Robotic Surgery ............................................................... 441 15.4 Autonomy Levels in Robotic Surgery ................................................................................. 442 15.5 Case Studies ......................................................................................................................... 443 15.5.1 Automated Ear Surgeries .........................................................................................443 15.5.2 Reconfigurable and Hyperredundant Robotic Platforms .......................................446 15.6 Conclusion and Future Trends ............................................................................................ 447 References .................................................................................................................................... 447
15.1 Overview of Robotic Surgery Robotic surgery is one of the fastest developing areas within the biomechatronics field, as it provides certain advantages to both surgeons and patients. From the perspective of surgeons the robotic systems may improve both safety and effectiveness of procedure, as well as reduce the physical and cognitive effort thus helping alleviate tiredness, especially in suture-intensive operations. From the perspective of the patients, robotic surgery usually means less postoperative pain, shorter hospital stays and less damage to tissues. According to [1], the first robotic minimally invasive surgery (MIS) was performed in 1987 in the form of laparoscopy. Laparoscopy is a surgical procedure in which a fiber-optic instrument is inserted through the abdominal wall to view the organs in the abdomen or permit small-scale surgery. Since then, the robotic MIS has been accepted in many Biomechatronics. https://doi.org/10.1016/B978-0-12-812939-5.00015-X © 2019 Elsevier Inc. All rights reserved.
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operations involving urology [2], brain and neural system, reproductive system [3], gastronomical, and cardiovascular tracts. Some of these operations do not even need an incision such as natural orifice transluminal endoscopy (NOTE) [4].
15.1.1 Introduction: Traditional Robotic Surgery Surgical robots assist during surgical procedures. They have been used since the mid1980s. Today, the majority of prostatectomies in the United States are robot-aided procedures as chances for successful operation are higher with robotic aid than without. Robotic surgeries are typically minimally invasive. This feature has been around long before the introduction of robots. It is a broad concept that encompasses many common procedures, such as a laparoscopic cholecystectomy, or gall bladder excisions. The procedure refers to a method that avoids long cuts by operating on the body through small (usually 1 cm) entry incisions. Surgeons use long-handled instruments to operate on tissue within the body. Such operations are guided by viewing equipment called endoscopes. These are thin tubes with a camera attached to the end of it that allows the surgeon to view highly magnified real-time three-dimensional images of the operation site on a monitor. The current benefits of robotic surgery include better accuracy, precision, dexterity, tremor corrections, scaled motion, and more recently haptic corrective feedback. These benefits result in more successful surgeries and smaller necessary incision cuts. Overall, the robotic systems have better accuracy and precision than unaided surgeons. Surgical robots are able to position the surgical tools closer to the “right spot” and deviate less from the “right trajectory.” The robot’s end-effectors can be much smaller and more dexterous than a human hand. They can record and filter out a surgeon’s natural hand tremor and rescale movement to increase precision and reduce the chance for error. Lastly, the robot could restrain the surgeon’s movement into undesired directions through haptic feedback. Researchers are formulating new ways to address motion and tissue resistance. For example, the surgical robot could synchronically move with a beating heart such that their relative speed is close to zero. Another possible improvement is the ability for the robot to automatically adapt to the dynamical tissue resistance over time as the sensitivity scale of these processes goes beyond human capabilities. Typically, robotic surgery can be classified as either (i) supervisory-controlled, (ii) telesurgical, or (iii) shared-controlled. The supervisory-controlled approach is the most automated of the three methods. The RoboDoc from Integrated Surgical Systems Inc. is an example of a supervisory-controlled system used in orthopedic surgeries. After the surgeon positions the RoboDoc’s bonemilling tool at the correct position inside the patient, the robot automatically cuts the bone to just the right size for the orthopedic implant. Prior to the surgical procedure, the surgeon needs to prepare the operation through the planning and registration phase. In the planning phase, images of the patient’s body are
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used to determine the right surgical approach. Common imaging methods include computer tomography (CT) scans, magnetic resonance imaging (MRI) scans, ultrasonography, fluoroscopy, and X-ray scans. Next, in the registration phase, the surgeon must locate the points on the patient’s body that correspond to the images created during the planning phase. These points are matched to a 3D model, which can be updated by images seen through cameras or other real-time imaging techniques during surgery. After the robot finds the best fit between the model and reality, the surgical procedure is performed. The tele-surgical approach allows the surgical robot to be tele-operated, that is, operated from a distance by a human surgeon. In practice, the robot and the surgeon are only a couple of meters apart. Tele-operation is also possible across larger distances. However, problems such as time delays (i.e., tele-surgical latencies) and the available bandwidth (i.e., the amount of information that can be transferred per unit time) need to be considered. The tele-surgical approach is used by the da Vinci Surgical System, which was invented by Philip S. Green and developed by Intuitive Surgical Inc. This system currently dominates the surgical robot market. Initially dubbed Mona (after Leonardo’s Mona Lisa), the system was rechristened the da Vinci Surgical Robot in 1999; according to Mr. Green “…in honour of the man who had invented the first robot.” Although da Vinci never invented or built a real robot (credit for that goes to Tesla), he made many drawings of various mechanisms. The da Vinci System consists of three primary components: (1) a viewing and control console that is used by surgeon, (2) a vision cart that holds the endoscopes and provides visual feedback and (3) a surgical robot’s manipulator arm unit that includes three or four arms, depending on the model. The instruments that are attached to the arms are highly specialized. Functions for them include clamping, cutting, suturing, tissue manipulation, cauterizing, etc. It takes some time for surgeons to get accustomed to the da Vinci System. According to a study, even with initial training program, provided by the Intuitive Surgical, it takes about 12–18 operations before surgeons feel comfortable performing the procedure. Often, during this period, surgeons complain on lack of tactile force feedback or ability to “feel” the tissue. The shared-controlled approach refers to the method by which the robot is not just motion tele-operated as it can decide to resist the surgeons’ intended movement if it deems that it would not be beneficial. Typically, the work space is split into several segments and the system behaves differently based on different localization according to safe, close, boundary, or forbidden classification. For example, if surgeon moves a cutting tool in the direction of tissue that should not be damaged, the robot will apply the force haptic feedback that will grow stronger as the cutting tool comes closer to the fragile tissue. In other words, here, surgeon again “feels” the virtual representation of tissue that may have preprogrammed specifications different from the real tissue as well as somewhat different localization in space.
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15.1.2 Multiarm, Hyperredundant, Continuum, and Soft-Robotic Platforms for Robotic Endoscopy Although the first widely used and FDA approved robotic platforms for surgery were based on industrial six degrees of freedom (DOF) serial and rigid robotic manipulator such as [5], the robotic platforms are currently often designed with more DoF and with some level of flexibility. The hyperredundant robots with more DoF and dexterity are proposed to address difficult passages. Theoretically, a continuum robotic platform has infinite number of DoF and hence it is anticipated to be able to improve surgical procedures still further. Besides, the tubular/telescopic continuum robotic platforms can be miniaturized easily due to their simple mechanic construction. Further improvement to surgical platforms can be obtained by employing the inherent compliance of the soft materials. This chapter addresses above mentioned aspects and reviews some of multiarm, hyperredundant, continuum, and soft-robotic platform examples from literature and case studies from selected research laboratories. The forerunners of robotics surgical systems are endoscopic platforms since the inception of this field. An endoscopic process typically involves a small incision through which the rigid or flexible endoscopic devices is inserted to provided view on the tissue that is being operated. Because the insertion point/trocar limits the movement of the robotic arm in two directions, see for example Ref. [6], the remaining DOF for the endoscopic robotic platforms are totaled to four DOF (see Fig. 15.1). Although this usually limits the dexterity and manipulation of the end effector, endoscopic robots are still advantageous because they cause less pain, have a better cosmetic look after the operation, and the cost is much lower. In Ref. [6], a comprehensive classification of endoscopes is given including the categories of laparoscopes with or without camera, the manipulator size, and if the sterilization is possible.
FIG. 15.1 Reduced DOF for endoscopic tool after insertion [6].
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FIG. 15.2 (A) Overview of MASTER system and (B) structure of the slave manipulator. Original illustration by P. Boyraz.
A consensus by European Association of Endoscopic Surgeons (EAES) was reached in 2014 [7] defining the types of operations that can be performed using robotic endoscopy and the related requirements for safe and efficient execution. Ref. [8] summarizes robotic flexible endoscopy platforms for diagnosis and treatment of gastrointestinal diseases according to articles accessible through PubMed published between 2010 and 2015. According to that review Neoguide (Intuitive Surgical, United States) is FDA approved while commercially available robotic flexible endoscopic platforms include: Invendoscope (Invendo Medical Gmbh, Germany), Aer-O-scope (GI View Ltd, Israel), Endotics (ERA Endoscopy SRL, Italy), Endomina (Endo Tools Therapeutics, Belgium), and Viacath (Hansen Medical, United States). The other notable system mentioned in this review is MASTER (EndoMASTER Pte, Singapore) system, presented in Ref. [9] in adequate detail (see Fig. 15.2). This robotic system has a master and a slave manipulator driven by tendon-sheath actuation. The system also supports force-feedback for the surgeon. Clinical study involving 42 patients that undertook endonasal trans-sphenoidal surgery has been reported in Ref. [10]. There, a rigid endoscope is used with iArmS robotic platform as a support robot. More advanced applications of robots in endoscopy involve flexible robotic platforms [11] and endoscopic capsules (ECs) [12]. As discussed in Ref. [11], the ideal robotic endoscope has not been realized yet as there are numerous challenges that need to be overcome especially for flexible endoscopes. These challenges are mainly concerning the use of the robots for manipulation of the endoscopes themselves for the remote insertion and incorporation of such robots not only for NOTE type of operations but also for endoscopic submucosal dissection (ESD). The setup for flexible endoscopic application development is shown in Fig. 15.3. As a frontier in robotic endoscopy, the ECs [12] can open a new solution window to the problems with tethered and rigid systems. The first applications of EC were aimed at the drug delivery and diagnosis; however, recently they are being developed for the operational purposes. The operative capabilities of ECs are still under development and the movement of the device is usually provided by an external magnet.
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FIG. 15.3 The setup for flexible endoscopic application development [11]. Original illustration by P. Boyraz.
15.2 Platform-Based Classification of Robotic Surgery In this section, the robotic platforms used as autonomous, semiautonomous or assistive systems in the operations are classified based on the structure. The robotics platforms may increase the number of DoF either by addition of robotic arms to form multiarm structure, discussed in Section 15.2.1, or by having hyperredundant backbones, discussed in Section 15.2.2. In terms of minimizing the dimensions and having almost limitless DOF, the continuum robotics is considered in Section 15.2.3. Recent research focused on soft robotics in the context of robotics surgery is addressed in Section 15.2.4. Several examples of hybrid systems that may eventually lead to general robotic platform benefiting from increased DoF, compact structure and inherent compliance altogether are reviewed in Section 15.2.5.
15.2.1 Multiarm Robotic Platforms for MIS Over the last several decades there was a steady progress that finally led to sophistication of current gold standard in robotics surgery field in the form of the da Vinci Surgical System (Intuitive Surgical, Sunnyvale, CA, USA); detailed overview of these early historical developments is provided in Ref. [13]. In fact, the surgeons in the operation room need assistance from the other surgeons or staff nurse to hold some of the gripper carrying manipulators, endo-luminal devices or guidance catheters while they operate on the tissue with minimal stress and maximum safety. Therefore, the obvious and very first use of the robotics in the surgery has been the adaptations of the robots as third arm [14] or use multiple-arms of robotic platforms for dexterous manipulation [15]. There are even some cases in which the multiarm robot is used for a very specific surgical operation requiring three dimensional (3D) navigation
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and involving bone grafting [16]. Although being beneficial and safer, the multiarm robotic platforms have some disadvantages considering the need and cost of the optimization for the configuration space according to the patient’s body and the operable area [15]. Because of such disadvantages and costly installation/optimization process, other alternatives such as hyperredundant robot-arms and continuum robotic platforms are proposed. These two specific design ideas will be detailed in the next sections.
15.2.2 Hyperredundant Robotic Platforms Robotic platforms of the hyperredundant or piece-wise continuum design mostly use rigid or semirigid backbones. Recently proposed hyperredundant modular structures can be found in Refs. [17–19]. In Ref. [17], high dexterity and high-stiffness requirements for actual operation are provided although the design has limited compliance. The design in Ref. [17] also has intricate mechanical structure which can be difficult to miniaturize for medical applications required to work in limited operation space. More advanced prototypes can have control over the stiffness [18], however, they may have poorer modulebased controllability. Even though it is possible to have applications with better control [19] featuring continuum elastic backbone while segmenting the structure into modules with coupling plates, the compactness cannot be guaranteed. Most hyperredundant platforms have cable driven structures because they are lightweight and compact. However, there is an inherent limitation of such mechanisms due to cable friction and interdependency between the sections of the modules. Early examples of hyper-redundant manipulators with full solution on kinematics and dynamics are presented in Refs. [20–22]. Although the kinematics and dynamics are widely studied, the relevant control algorithms suggested for such mechanisms are not mature. For example, a modular control scheme is proposed in Ref. [23] with some promising results, however, more research efforts are needed in control aspect of hyperredundant manipulators. In that respect, the work in Ref. [24] presents a hybrid motion/force control application. Although the actual algorithm is developed for multibackbone continuum robots, it can be modified for hyperredundant robotic platforms using simplified kinematics. What is more exciting in hyperredundant platforms’ research is that very recent developments are taking place providing controllable stiffness in robotic arms. In Ref. [25], the researchers proposed such a platform to be used in laparo-endoscopic single-site surgery. The structure can be switched between five DOF rigid status to seven DOF compliant status according to the task required in the operation (see Fig. 15.4).
15.2.3 Continuum Robots for MIS A comprehensive survey on the continuum robots for medical applications [26] can guide the reader on which type of surgical interventions these type of robots should be preferred. A continuum robot has infinite DOF and can be driven by cables, hydraulic actuation or shape-memory-alloys based on the application and the level of required miniaturization.
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FIG. 15.4 The hyperredundant robotic arm with an adjustable section employing PCM alloy for the stiffness control via temperature change. Original illustration by P. Boyraz prepared based on J. Wang, S. Wang, J. Li, X. Ren, R.M. Briggs, Development of a novel robotic platform with controllable stiffness manipulation arms for laparoendoscopic single-site surgery (LESS), J. Med. Robot. Comput. Assist. Surg. 14 (2018) 1–16.
In Ref. [27] a co-centric tube type of robot is proposed using piezoelectric actuation. The co-centric tube type of continuum robots needs to be precurved according to their task and workspace in the operation. This might turn to be a disadvantage if the same medical device is desired to be used on different patients requiring different operational workspace. In addition, this type of continuum platforms may have limited capabilities of translational motion. A novel continuum manipulator design using serially connected double-layer planar springs [28] overcome these disadvantages to some degree (see Fig. 15.5). In addition, the proposed structure behaves like a helical spring, but its contraction and bending motion are decoupled, therefore easier to control.
15.2.4 Soft Robotics for Surgical Applications Soft-material robotic platforms open up a new path for obtaining compliant and safe platforms. A good example of such an application can be seen in Ref. [29]. In this work, the researchers used flexible fluidic actuators allowing dexterous and safe navigation. It was possible to overcome the restrictions that are normally posed in a situation where the rigid manipulator has to work in a cavity with multiple organs in close proximity. Fig. 15.6 depicts the advantage of the soft robot in terms of dexterity in a confined region.
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FIG. 15.5 A novel continuum robotic platform with multilayer deformable springs. Original illustration by P. Boyraz prepared based on P. Qi, C. Qui, H. Liu, J.S. Dai L.D. Seneviratne, K. Althoefer, A novel continuum manipulator design using serially connected double-layer planar springs, IEEE/ASME Trans. Mechatr. 21(3) (2016) 1281–1292.
FIG. 15.6 An illustration of dexterous advantage of the soft robot compared to rigid robot. Original illustration by P. Boyraz prepared based on H. Abidi, G. Gerboni, M. Brancadoro, J. Fras, A. Diodato, M. Cianchetti, H. Wurdemann, K. Althoefer, Highly dexterous 2-module soft robot for intra-organ navigation in minimally invasive surgery, Int. J. Med. Robot. Comput. Assist. Surg. 14 (2018) 1–9.
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Another work can be taken as a guiding example for planning the navigation or locomotion of such robots in tubular environments [30]. Although the application is generic, it can be easily modified for cardiovascular or urological interventions because it prevents full occlusion of the tubular channel while navigating in it. This is a big advantage compared to traditional rigid structures as they tend to block such channels and in extreme cases cause tissue damage.
15.2.5 Hybrid Robotic Platforms The hybrid robotic platforms strive to combine the best properties of serial rigid robotic arms with continuum and/or soft robots to achieve superior qualities such as position accuracy and compliancy at the same time. For example, the system described in Ref. [31] comprises of a serial manipulator which is connected to a continuum platform. In this combined hybrid structure the robot was observed to have superb positioning and tracking accuracy. A conceptual design of the hybrid robotic platform can be seen in Fig. 15.7. Normally, when entering into human body through the incision, two DOF provided by the rigid arm are sacrificed. However, in this setup it can be regained, thanks to the flexible continuum robot at the end. Herein, the word “hybrid” can also refer to the combination of serial and parallel links (i.e., open and closed kinematic chains) to form a better spatial capability for the end effector [32]. Another possibility of obtaining a hybrid platform is to combine the continuum structures with soft materials, as seen in Ref. [33], incorporating also reconfigurability. This hybrid platform (see Fig. 15.8), although not used in medical robotics yet could be easily adapted to many surgical applications, provided that it can be manufactured in smaller dimensions.
FIG. 15.7 Hybrid robotic system combining a flexible continuum robot and a rigid 6 DOF robotic arm [31]. Original illustration by P. Boyraz.
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FIG. 15.8 Soft compliant manipulator with continuum segments, SIMBA [26]. Original illustration by P. Boyraz.
15.3 Human-Machine Interaction in Robotic Surgery One of the grand challenges of the robotic surgery nowadays is in the area of designing efficient and ergonomic human-machine interaction (HMI) systems to improve the augmentation of the surgeon and the robot. Considering that not all the surgical platforms could be fully autonomous, HMI systems will always be needed in the operation rooms to facilitate the integration of robotic tools for surgery. A reasonable starting point of such technology involves the virtual-reality applications [34] to simulate the high-skill tasks for surgeons such as suturing. A more direct application of HMI systems could be teleoperated surgical systems. A recent and exciting example of such a system uses a haptic interface to manipulate and steer miniaturized untethered soft-magnetic grippers in Ref. [35]. In addition to new HMI system designs in robotic surgery, observing the human factors and ergonomics criteria is also very important. For example, in Ref. [36], human arm stiffness is examined during the virtual tele-operation of robotic manipulators. In that study, the researchers have proposed a nondisruptive method to study the stiffness of the human arm during different tasks within an operation. This type of performance analysis is required and must be performed to assess the stability and precision of the execution of the task, because the overall system is a combination of the human skills incorporated with the robotic system’s dynamics. The collaborative robots could be considered as being on the very top of HMI research in the robotic surgery field. These systems are aimed at providing the surgeon more stable assistance, especially in effort-laden suture procedures. An example of such a system is detailed in Ref. [37]. This type of system must have the capability to recognize surgical gestures made by surgeon and should have an algorithm supporting the autonomous decision-making. The experimental setup for the proposed collaborative system is presented in Fig. 15.9.
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FIG. 15.9 Experimental setup for development of collaborative robot platform. Original illustration by P. Boyraz prepared based on E. Bauzano, B. Estebanez, I. Garcia-Morales, V. Munoz, Collaborative human-robot system for HALS suture procedures, IEEE Syst. J. 10(3) (2016) 957–966.
15.4 Autonomy Levels in Robotic Surgery As with any system that is gradually evolving into autonomous operation modes, the surgical robots are also under development to make that transition in a safe manner. As it is also realized on time by the authorities, a new ISO standard has been compiled defining the autonomy levels in medical equipment [38]. In addition to standardization efforts by experts and authorities, the research community is also responding via well-funded research projects such as I-SUR (EU FP7 funded, Intelligent Surgical Robotics). In this project, the researchers developed innovative solutions [39] such as surgical planning and execution of movement of robot arms in contact with a deformable environment, an interface minimizing the cognitive load of the surgeon through supervision of the actions and intraoperative sensing together with reasoning to detect the transitions between the autonomous and tele-operated modes. In fact, in Ref. [40] this transition is detailed using a two-layered bilateral control, stabilizing the process of authority transition from robot to surgeon. More focused studies also exist, for example, integrating human surgeon in an automated suturing task as seen in Ref. [41]. In that study, the researchers were able to accelerate the suturing process by 79% using one-master and two-slave system with force sensing. The autonomous suturing process can be seen in Fig. 15.10.
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FIG. 15.10 Human-integrated autonomous suturing process. Original illustration by P. Boyraz prepared based on K. Watanabe, T. Kanno, K. Ito, K. Kawashima, Human-integrated automation of suturing task with one-master two-slave system for laparoscopic surgery, IEEE Int. Conf. on Advanced Intelligent Mechatronics (AIM), Banf, Alberta, Canada, 2016.
In order to execute a semiautonomous surgical process, task recognition is necessary for the surgical robot. In Ref. [42], a distance-based time series classification is used for task recognition. The recognition output is used to adjust the position of the camera upon recognizing the surgeon’s movements in terms of kinematic time series. Using the (dis) similarity measures between the tasks, the robot is able to distinguish for example, the task of suturing from needle passing or knot tying movements.
15.5 Case Studies 15.5.1 Automated Ear Surgeries Surgical manipulations of the ear, such as ones for implantable hearing aids, are able to help patients with hearing deficiencies. However, such operations require access to the middle and/or inner ear, which involves drilling a cavity into the mastoid (mastoidectomy), the skull bone behind the ear. Such manual procedures produce openings physically much larger (several centimeters) than optimally required for the insertion of the implantable hearing aid (a few millimeters), and this is done primarily to obtain visual access to underlaying key landmark features, used to help locate the target location, while navigating away from critical anatomical structures that should not be harmed. Even if the
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incision opening would be much smaller, the tool trajectory still needs to pass through a window of a few millimeters, where all critical biological structures and tissues are located. Thus, a precision smaller than 0.5 mm is needed for planning, navigation, guidance during operation. There are several existing solutions to this challenge that have been applied in clinical and in vitro conditions, however all share common crucial procedural steps. Below is a brief overview of some of the existing solutions with emphasis on the common as well as unique parts of their methodology. One solution to this problem [43] is based on the concept of a stereotactic frame, custom build for each individual operation and patient, which aids the guidance of the drilling instrument during the surgical procedure, in order to precisely reach the target location while avoiding crucial anatomical structures. The procedure consists of five major steps. The procedure starts with attachment of fiducial markers, in the form of bone anchored percutaneous screws, to the patient’s head, surrounding the mastoid (the surgical access area). The design of the screws is such that they are clearly visible in the X-ray domain, and have a well-defined point of contact, accessible for physical contact with a registration tool. During the second step, the patient’s head is preoperatively scanned using a medical X-ray computed tomography (CT) scanner, with a voxel size of approximately 0.3 mm, depending on the scan conditions. In the third step, the volumetric scan data is then analyzed, crucial anatomical features and structures are identified, and the geometry of the anchor screws is registered relative to their CAD model. Based on all these features, a preoperative planning is made, where the drilling trajectory, defined by the target (final) and entry locations, for the surgical procedure is established such that the anatomical structures, including the facial nerve and major blood vessels, are safely avoided. The anatomical feature segmentation and identification as well as the trajectory planning, is performed automatically in a matter of minutes, and the resulting trajectory is verified by a surgeon [44]. In the fourth step, custom stereotactic frame is manufactured such that it provides attachment points for custom legs, which anchor the frame to the screws in the skull. The stereotactic frame also features a channel to guide a medical drill along the preoperatively defined surgical entry trajectory, virtually defined in the previous step. The frame could be manufactured through means of rapid prototyping [45], which, while appealing for its ease of use, proved to be time consuming (48-h lead time) as it doubles or triples the total procedural time. This delay has been overcome, by modifying the design of the stereotactic frame to allow it to be manufactured by more traditional manufacturing techniques (e.g., via a CNC milling machine) on site, which decreases the leadtime down to a few minutes. In the final step, the stereotactic frame is attached to the anchor screws at the patient’s head. Once the frame is firmly secured, the drilling can commence. Tests so far indicate drill jitter of approximately 70 μm on average, with target and trajectory accuracies in the order of 0.4 mm, verified in vitro. Total time for steps 2–4, which are at the core of the automated surgical process, is approximately 30 min. During the drilling process, a typical drill size of 1 mm diameter is used, which leaves <1 mm (sometimes <0.5 mm) of clearance from crucial anatomical structures to be avoided, as
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FIG. 15.11 Overview of a virtual trajectory definition with tolerance and minimal distances to crucial anatomical structures to be avoided during the drilling procedure. Original illustration by P. Boyraz prepared based on N. Gerber, B. Bell, K. Gavaghan, C. Weisstanner, M. Caversaccio, S. Weber, Surgical planning tool for robotically assisted hearing aid implantation, Int. J. Comput. Assist. Radiol. Surg. 9(1) (2014) 11–20.
shown in Fig. 15.11. The generality of such a procedure allows its application to a great variety of surgical procedures in the head, where the skull provides solid points for anchoring of the stereotactic frame. While accurate, the above-mentioned approach to registration, between the physical space (patient and surgical tool) and virtual planning (CT scan data and trajectory), relies on semi-manual manipulation (assembly and adjustment of the stereotactic frame), which leaves room for an accidental error. This has been further improved in the approaches of two other independent research groups [46, 47], where the physical stereotactic frame has been substituted with an optical [46] or electromagnetic [40] tracking system, which provides precise (below 100 μm) location of the tool relative to the patient, via bone anchored fiducial screws. In addition, five or six DOF serial robotic manipulator is incorporated into the overall procedure to provide accurate and consistent way of holding and moving the surgical drilling tool intraoperatively. The combination of a robotic manipulator and an automatic guidance system allows for a fully automated execution of the registration with the patient’s head and drilling via a predefined trajectory. In addition, one of the systems [47] includes a load cell at the tool holder interface to provide information on the exerted manipulation forces, which allows tele-operated haptic control mode, during which a surgeon guides the robot via a force-feedback controller. While such mode of operation seems to add additional complexity to the overall setup and procedure, it is a crucial feature for the adoption of such technologies, allowing further development and optimization.
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15.5.2 Reconfigurable and Hyperredundant Robotic Platforms In this part, the design of hyperredundant and modular robotic structures is detailed by emphasizing their features such as independent module/segment controllability and variable-adjustable stiffness. The proposed designs [48] are aimed at improving both position and force control of such structures employing whole-body shape control and local stiffness control in the robotic catheter on module basis. Three different module designs for hyperredundant mechanisms are depicted in Fig. 15.12. The first mechanism is called ‘hybrid’ comprising a universal joint placed in between two parallel plates. This mechanism has three DOF per module, having pan and tilt for adjusting the heading angle while using the translational movement to shrink or elongate while adjusting its stiffness. The helical spring around the middle shaft provides inherent compliance for the module. The second mechanism is 3 SPS having spherical-prismatic-spherical joints in each strut can be considered as a reconfigurable parallel mechanism. It provides stiffness adjustments by relocating the connection points of the struts on the lower plate. The struts can also elongate and contract along their axis so that the hyperredundant platform can be adjusted when passing along difficult cavities. Finally, the last module is named after the seahorse tail since it is inspired by the cross section of the biological structure. This mechanism can radially change dimensions in a similar manner of seahorse tail structure, using the oblique muscles. The modules are connected by a spherical joint in the middle. Since the radial struts are spring-loaded, therefore, the radial stiffness can be adjusted. The main advantage of reconfigurable hyperredundant mechanisms is that each segment can be controlled separately, and the multidegree-of-freedom makes it possible to control the whole-body shape of the manipulator to reduce the risk of harming the tissues during the navigation task. If the modules also have variable stiffness or reconfigurability as it is shown here, the versatility and the safety of the hyperredundant platforms increase. Since robotic platforms should accomplish tasks such as navigation, diagnosis, and operation they may have to support different levels of stiffness.
FIG. 15.12 Modules for hyperredundant backbone construction, from left to right: Hybrid-module, radially reconfigurable 3 SPS parallel-kinematic mechanism, and seahorse tail section [48].
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15.6 Conclusion and Future Trends Robotic surgery has reached a certain maturity level in terms of application-specific solutions using multiple-arm robots and employing master-slave systems. However, several ongoing research directions involving for example soft-robotics, human-robot collaboration, and the transition to higher levels of autonomy, hold a promise to still further advance this field. Another trend for surgical robotics include micro-robots that could be delivered in gastrointestinal or cardiovascular tract to perform certain surgical operations, however, up to date research has only achieved a mesoscale prototype that could both navigate in torturous channels and perform an operation, which may require certain force levels. In summary, the field of surgical robotics is still an active area of research with the aim of obtaining minimal invasiveness while achieving autonomous navigation and operation. The rapidly developing field of robotic surgery will also cause the rethinking of the role of surgeons in the operation room. While surgical robots could help in achieving more reliable, faster and standardized procedures, they will be still controlled (in fully manual or semiautonomous mode) by the surgeons, who will need to expand their field of expertise and knowledge, to use more efficiently the capabilities of such robotic systems. Surgeon will be still a key figure in the operating theater; however, surgeon’s role will expand into augmenting existing surgical procedures or even designing completely new ones utilizing emerging novel systems. As the range of capabilities of surgical robotics expands, so will grow the importance of experienced surgeons to adopt new technologies and further advance the efficiency and success rate of surgical procedures.
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