Venkata Sreekanth Arikatla

Plugfest 2009: Global interoperability in Telerobotics and telemedicine

Despite the great diversity of teleoperator designs and applications, their underlying control systems have many similarities. These similarities can be exploited to enable inter-operability between heterogeneous systems. We have developed a network data specification, the Interoperable Telerobotics Protocol, that can be used for Internet based control of a wide range of teleoperators. In this work we test interoperable telerobotics on the global Internet, focusing on the telesurgery application domain. Fourteen globally dispersed telerobotic master and slave systems were connected in thirty trials in one twenty four hour period. Users performed common manipulation tasks to demonstrate effective master-slave operation. With twenty eight (93%) successful, unique connections the results show a high potential for standardizing telerobotic operation. Furthermore, new paradigms for telesurgical operation and training are presented, including a networked surgery trainer and upper-limb exoskeleton control of micro-manipulators.

Preliminary Face and Construct Validation Study of a Virtual Basic Laparoscopic Skill Trainer

BACKGROUND The Virtual Basic Laparoscopic Skill Trainer (VBLaST) is a developing virtual-reality-based surgical skill training system that incorporates several of the tasks of the Fundamentals of Laparoscopic Surgery (FLS) training system. This study aimed to evaluate the face and construct validity of the VBLaST system. MATERIALS AND METHODS Thirty-nine subjects were voluntarily recruited at the Beth Israel Deaconess Medical Center (Boston, MA) and classified into two groups: experts (PGY 5, fellow and practicing surgeons) and novice (PGY 1-4). They were then asked to perform three FLS tasks, consisting of peg transfer, pattern cutting, and endoloop, on both the VBLaST and FLS systems. The VBLaST performance scores were automatically computed, while the FLS scores were rated by a trained evaluator. Face validity was assessed using a 5-point Likert scale, varying from not realistic/useful (1) to very realistic/useful (5). RESULTS Face-validity scores showed that the VBLaST system was significantly realistic in portraying the three FLS tasks (3.95 +/- 0.909), as well as the reality in trocar placement and tool movements (3.67 +/- 0.874). Construct-validity results show that VBLaST was able to differentiate between the expert and novice group (P = 0.015). However, of the two tasks used for evaluating VBLaST, only the peg-transfer task showed a significant difference between the expert and novice groups (P = 0.003). Spearman correlation coefficient analysis between the two scores showed significant correlation for the peg-transfer task (Spearman coefficient 0.364; P = 0.023). CONCLUSIONS VBLaST demonstrated significant face and construct validity. A further set of studies, involving improvement to the current VBLaST system, is needed to thoroughly demonstrate face and construct validity for all the tasks.

The added value of virtual reality technology and force feedback for surgical training simulators

Laparoscopic surgery requires more specialized training of the surgeons than traditional open surgery. The Virtual Basic Laparoscopic Surgical Trainer (VBLaST) is being developed as a virtual version of the Fundamentals of Laparoscopic Skills (FLS) trainer. This study assessed the current haptic and virtual reality (VR) technology of a virtual peg transfer task of the VBLaST, based on the subjective preference of surgeons and their objective task performance measures. Twenty-one surgical residents, fellows and attendings performed a peg-transfer task in the FLS and the VBLaST. Each subject performed 10 trials on each simulator. Results showed that subjects performed significantly better on the FLS than on the VBLaST. Subjects showed a significant learning effect on both simulators, but with an accelerated improvement on the VBLaST. Even so, 81% of the subjects preferred the FLS over the VBLaST for surgical training which could be attributed to the novelty of the VR technology and existing deficiencies of the haptic interface. Despite the subjective preference for the physical simulator, the performance results indicate an added value of VR and haptics in surgical training, which is expected to be demonstrated in more surgically relevant tasks such as suturing and knot-tying.

A physics-driven neural networks-based simulation system (phynness) for multimodal interactive virtual environments involving nonlinear deformable objects

While an update rate of 30 Hz is considered adequate for real-time graphics, a much higher update rate of about 1 kHz is necessary for haptics. Physics-based modeling of deformable objects, especially when large nonlinear deformations and complex nonlinear material properties are involved, at these very high rates is one of the most challenging tasks in the development of real-time simulation systems. While some specialized solutions exist, there is no general solution for arbitrary nonlinearities. In this work we present PhyNNeSS—a Physics-driven Neural Networks-based Simulation System—to address this long-standing technical challenge. The first step is an offline precomputation step in which a database is generated by applying carefully prescribed displacements to each node of the finite element models of the deformable objects. In the next step, the data is condensed into a set of coefficients describing neurons of a Radial Basis Function Network (RBFN). During real-time computation, these neural networks are used to reconstruct the deformation fields as well as the interaction forces. We present realistic simulation examples from interactive surgical simulation with real-time force feedback. As an example, we have developed a deformable human stomach model and a Penrose drain model used in the Fundamentals of Laparoscopic Surgery (FLS) training tool box. A unique computational modeling system has been developed that is capable of simulating the response of nonlinear deformable objects in real time. The method distinguishes itself from previous efforts in that a systematic physics-based precomputational step allows training of neural networks which may be used in real-time simulations. We show, through careful error analysis, that the scheme is scalable, with the accuracy being controlled by the number of neurons used in the simulation. PhyNNeSS has been integrated into SoFMIS (Software Framework for Multimodal Interactive Simulation) for general use.

Towards virtual FLS: development of a peg transfer simulator

Peg transfer is one of five tasks in the Fundamentals of Laparoscopic Surgery (FLS), program. This paper reports the development and validation of a Virtual Basic Laparoscopic Skill Trainer‐Peg Transfer (VBLaST‐PT©) simulator for automatic real‐time scoring and objective quantification of performance.

A physics-based algorithm for real-time simulation of electrosurgery procedures in minimally invasive surgery.

High‐frequency electricity is used in the majority of surgical interventions. However, modern computer‐based training and simulation systems rely on physically unrealistic models that fail to capture the interplay of the electrical, mechanical and thermal properties of biological tissue.

Achieving interface and environment fidelity in the Virtual Basic Laparoscopic Surgical Trainer

Virtual reality trainers are educational tools with great potential for laparoscopic surgery. They can provide basic skills training in a controlled environment and free of risks for patients. They can also offer objective performance assessment without the need for proctors. However, designing effective user interfaces that allow the acquisition of the appropriate technical skills on these systems remains a challenge. This paper aims to examine a process for achieving interface and environment fidelity during the development of the Virtual Basic Laparoscopic Surgical Trainer (VBLaST). Two iterations of the design process were conducted and evaluated. For that purpose, a total of 42 subjects participated in two experimental studies in which two versions of the VBLaST were compared to the accepted standard in the surgical community for training and assessing basic laparoscopic skills in North America, the FLS box-trainer. Participants performed 10 trials of the peg transfer task on each trainer. The assessment of task performance was based on the validated FLS scoring method. Moreover, a subjective evaluation questionnaire was used to assess the fidelity aspects of the VBLaST relative to the FLS trainer. Finally, a focus group session with expert surgeons was conducted as a comparative situated evaluation after the first design iteration. This session aimed to assess the fidelity aspects of the early VBLaST prototype as compared to the FLS trainer. The results indicate that user performance on the earlier version of the VBLaST resulting from the first design iteration was significantly lower than the performance on the standard FLS box-trainer. The comparative situated evaluation with domain experts permitted us to identify some issues related to the visual, haptic and interface fidelity on this early prototype. Results of the second experiment indicate that the performance on the second generation VBLaST was significantly improved as compared to the first generation and not significantly different from that of the standard FLS box-trainer. Furthermore, the subjects rated the fidelity features of the modified VBLaST version higher than the early version. These findings demonstrate the value of the comparative situated evaluation sessions entailing hands on reflection by domain experts to achieve the environment and interface fidelity and training objectives when designing a virtual reality laparoscopic trainer. This suggests that this method could be used successfully in the future to enhance the value of VR systems as an alternative to physical trainers for laparoscopic surgery skills. Some recommendations on how to use this method to achieve the environment and interface fidelity of a VR laparoscopic surgical trainer are identified.

Virtual interactive suturing for the Fundamentals of Laparoscopic Surgery (FLS)

BACKGROUND Suturing with intracorporeal knot-tying is one of the five tasks of the Fundamentals of Laparoscopic Surgery (FLS), which is a pre-requisite for board certification in general surgery. This task involves placing a short suture through two marks in a penrose drain and then tying a double-throw knot followed by two single-throw knots using two needle graspers operated by both hands. A virtual basic laparoscopic skill trainer (VBLaST©) is being developed to represent the virtual versions of the FLS tasks, including automated, real time performance measurement and feedback. In this paper, we present the development of a VBLaST suturing simulator (VBLaST-SS©). Developing such a simulator involves solving multiple challenges associated with fast collision detection, response and force feedback. METHODS In this paper, we present a novel projection-intersection based knot detection method, which can identify the validity of different types of knots at haptic update rates. A simple and robust edge-edge based collision detection algorithm is introduced to support interactive knot tying and needle insertion operations. A bimanual hardware interface integrates actual surgical instruments with haptic devices enabling not only interactive rendering of force feedback but also realistic sensation of needle grasping, which realizes an immersive surgical suturing environment. RESULTS Experiments on performing the FLS intracorporeal suturing task show that the simulator is able to run on a standard personal computer at interactive rates. CONCLUSIONS VBLaST-SS© is a computer-based interactive virtual simulation system for FLS intracorporeal knot-tying suturing task that can provide real-time objective assessment for the users performance.

Towards immersive virtual reality (iVR): a route to surgical expertise.

Surgery is characterized by complex tasks performed in stressful environments. To enhance patient safety and reduce errors, surgeons must be trained in environments that mimic the actual clinical setting. Rasmussen’s model of human behavior indicates that errors in surgical procedures may be skill-, rule-, or knowledge-based. While skill-based behavior and some rule-based behavior may be taught using box trainers and ex vivo or in vivo animal models, we posit that multimodal immersive virtual reality (iVR) that includes high-fidelity visual as well as other sensory feedback in a seamless fashion provides the only means of achieving true surgical expertise by addressing all three levels of human behavior. While the field of virtual reality is not new, realization of the goals of complete immersion is challenging and has been recognized as a Grand Challenge by the National Academy of Engineering. Recent technological advances in both interface and computational hardware have generated significant enthusiasm in this field. In this paper, we discuss convergence of some of these technologies and possible evolution of the field in the near term.

A two-grid iterative approach for real time haptics mediated interactive simulation of deformable objects

Fast and efficient algorithms are paramount in any real-time multimodal interactive simulation involving soft deformable objects. To achieve real time computational rates, it is expedient to adaptively refine the simulation mesh in the vicinity of the interaction region instead of using a uniformly refined mesh. While appealing, such an approach is difficult to implement as the system of linear algebraic equations changes during the course of the simulation as the interaction region is dynamically updated. A direct solution approach for the discretized system of equations is, of course, computationally expensive hence iterative approaches must be pursued. In this paper, we present a novel two-grid computational methodology that uses pre-computed solution on a coarse grid representation of the geometry and a prolongation operator that transfers the coarse grid solution to a locally refined fine grid to generate the initial guess for a Gauss-Seidel type iterative solver. A local relaxation approach is then introduced that preferentially relaxes the local and global residuals and vastly improves computational efficiency, especially with increasing number of degrees of freedom of the mesh. Example problems demonstrate the effectiveness of the method.