We describe the implementation details of a real-time surgical simulation system with soft-tissue modeling and multi-user, multi-instrument, networked haptics. The simulator is cross-platform and runs on various Unix and Windows platforms. It is written in C++ with OpenGL for graphics; GLUT, GLUI, and MUI for user interface; and supports parallel processing. It allows for the relatively easy introduction of patient-specific anatomy and supports many common file formats. It performs soft-tissue modeling, some limited rigid-body dynamics, and suture modeling. The simulator interfaces to many different interaction devices and provides for multi-user, multi-instrument collaboration over the Internet. Many virtual tools have been created and their interactions with tissue have been implemented. In addition, a number of extra features, such as voice input/output, real-time texture-mapped video input, stereo and head-mounted display support, and replicated display facilities are presented.

This paper presents algorithms for animating deformable objects in real-time. It focuses on computing the deformation of an object subject to external forces and detecting collisions among deformable and rigid objects. The targeted application domain is surgical training. This application relies more on visual realism than exact, patientspecific deformation, but requires that computations be performed in real-time. This is in contrast with pre-operative surgical planning, where computations may be done offline, but must provide accurate results. To achieve realtime performance, the proposed algorithms take advantage of the facts that most deformations are local, human-body tissues are well damped, and motions of surgical instruments are relatively slow. They have been integrated into a virtual-reality system for simulating the suturing of small blood vessels (microsurgery).

The best method of training for laparoscopic surgical skills is controversial. Some advocate observation in the operating room, while others promote animal and simulated models or a combination of surgery-related tasks. A crucial process in surgical education is to evaluate the level of surgical skills. For laparoscopic surgery, skill evaluation is traditionally performed subjectively by experts grading a video of a procedure performed by a student. By its nature, this process uses fuzzy criteria. The objective of the current study was to develop and assess a skill scale using Markov models (MMs). Ten surgeons [five novice surgeons (NS); five expert surgeons (ES)] performed a cholecystectomy and Nissen fundoplication in a porcine model. An instrumented laparoscopic grasper equipped with a three-axis force/torque ( ) sensor was used to measure the forces/torques at the hand/tool interface synchronized with a video of the tool operative maneuvers. A synthesis of frame-by-frame video analysis and a vector quantization algorithm, allowed to define signatures associated with 14 different types of tool/tissue interactions. The magnitude of applied by NS and ES were significantly different ( 0 05) and varied based on the task being performed. High magnitudes were applied by NS compared with ES while performing tissue manipulation and vise versa in tasks involved tissue dissection. From each step of the surgical procedures, two MMs were developed representing the performance of three surgeons out of the five in the ES and NS groups. The data obtained by the remaining two surgeons in each group were used for evaluating the performance scale. The final result was a surgical performance index which represented a ratio of statistical similarity between the examined surgeon 's MM ...

. Computer systems for surgical planning and training are poised to greatly impact the traditional versions of these tasks. These systems provide an opportunity to learn surgical techniques with lower costs and lower risks. We have developed a virtual environment for the graphical visualization of complex surgical objects and real-time interaction with these objects using real surgical tools. An application for microsurgical training, in which the user sutures together virtual blood vessels, has been developed. This application demonstrates many facets of our system, including deformable object simulation, tool interactions, collision detection, and suture simulation. Here we present a broad outline of the system, which can be generalized for any anastomosis or other procedures, and a detailed look at the components of the microsurgery simulation. 1

Abstract. Robotic surgical systems such as Intuitive Surgical’s da Vinci system provide a rich source of motion and video data from surgical procedures. In principle, this data can be used to evaluate surgical skill, provide surgical training feedback, or document essential aspects of a procedure. If processed online, the data can be used to provide contextspecific information or motion enhancements to the surgeon. However, in every case, the key step is to relate recorded motion data to a model of the procedure being performed. This paper examines our progress at developing techniques for “parsing ” raw motion data from a surgical task into a labelled sequence of surgical gestures. Our current techniques have achieved>90 % fully automated recognition rates on 15 datasets. 1

Computer simulation of surgery and scientific experiments help in preparation, training, and assessment. These benefits can be further extended with the integration of robotics for teleoperation and assistance. We describe our efforts to build a realistic and useable simulation for astronaut training and experiment planning. Most of our development focused on user interaction with hand sensors, a necessary component for realism. For the hands, we developed a simulation and focused on aspects of fine tuning the registration and calibration to increase realism and functionality. This proved to be a necessary basis to integrate robotics and further the simulation's range of applications. Accurate registration, calibration, and robotic integration helped build a foundation for a useable simulation for astronaut training on ground and avenues of robotic assistance during flight.

The present study examined the effect of vibrotactile feedback in a needle-insertion task using a surgical robot. Four participants performed the task by hand (using a manual needle driver instrument) and by using a surgical robot, with or without vibrotactile feedback. The vibrotactile feedback signal indicated the deviation in force direction, with the signal amplitude modulated by the force magnitude. Visual feedback was always available in all experimental conditions. The participants ’ task was to insert a hooked needle into a simulated tissue pad at a premarked entrance point and drive it out of the tissue pad at a corresponding pre-marked exit point. The participants were instructed to hold the hooked needle in an orientation that minimized side-loading on the simulated tissue pad and prevented needle rotation in the needle driver. The forces exerted by the needle on the simulated tissue pad were recorded. The results indicated that the vibrotactile display was useful in reducing the overall force-direction deviation during the needle-insertion task, but it increased task completion time. It generally took twice as long to perform the task with the robot than with the hand. One participant who was experienced with the surgical robot consistently applied less force with the robot than with the hand. The vibrotactile feedback reduced the magnitude of the force component that was perpendicular to the suturing surface, but not the forces along the suturing surface. We compare our results to those reported in the literature and discuss the challenges we faced in assessing haptic feedback in a skilled surgical task such as the one used in the present study.

Abstract—The paper presents an investigation into the role of virtual reality and web technologies in the field of distance education. Within this frame, special emphasis is given on the building of web-based virtual learning environments so as to successfully fulfill their educational objectives. In particular, basic pedagogical methods are studied, focusing mainly on the efficient preparation, approach and presentation of learning content, and specific designing rules are presented considering the hypermedia, virtual and educational nature of this kind of applications. The paper also aims to highlight the educational benefits arising from the use of virtual reality technology in medicine and study the emerging area of web-based medical simulations. Finally, an innovative virtual reality environment for distance education in medicine is demonstrated. The proposed environment reproduces conditions of the real learning process and enhances learning through a real-time interactive simulator.

In this paper we present our initial work on simulating suture and suturing using mass-spring models. Various models for simulating suture were studied, and a simple linear mass-spring model of the suture was determined to give good performance. A novel model for pulling a suture through a deformable surface is presented. By connecting two separate surfaces through the suture, our model can simulate a suturing task. The results are shown using software we developed that runs on a standard PC and models the action of a suturing device used in minimally invasive Laparoscopic surgery.

Clinical medicine is one of the most chal-lenging areas for education. The develop-ment of clinical competence requires the assimilation of large amounts of knowl-edge combined with acquisition of clinical skills and clinical problem-solving ability. Clinical skills include the technical skill in implementing a procedure as well as skill in patient consultation and physical exami-nation. Clinical problem solving requires the ability to synthesize the information contained in a clinical case and to integrate it with the physician’s knowledge and experience in order to diagnose and manage the patient’s problem. It also requires the ability to work in teams and the ability to transfer one’s knowledge to unfamiliar situations such as rare problems, disasters and emergencies. Currently, training toward clinical competence follows an apprenticeship approach, which consists of close expert supervision while interacting with patients. This method of training can subject patients to discomfort, risk of complications, and prolonged procedure times, creating a clinical governance dilemma. At the same time, there may be limited access to apprenticeship training in more complex sce-narios with corresponding difficulty training in a time-effective manner. Intelligent clinical training systems hold the promise to address many of these issues. A facilitating technological environment has emerged in recent years through the maturation of research in intelligent tutoring systems, medical simulation, and virtual reality (VR) techniques and the develop-