In the area of surgical robotics no standard means of performance evaluation has been established. Thousands of surgeons have gone through the SAGES FLS Program, and the psychomotor skill portion of the program is considered the gold standard in laparoscopic skills evaluation. This research describes the use of the FLS block transfer task to evaluate the performance of both surgeons and non-surgeons teleoperating under different time delay conditions on the University of Washington RAVEN Surgical Robot. Time delays of 0 ms, 250 ms, and 500 ms were used and a statistically significant difference in mean block transfer time as well as mean tool tip path length were shown. For this task no significant difference was shown between the surgeon and non-surgeon groups. Clearly surgeon input and feedback is key to surgical robotic system development, but this result implies that non-surgeon subjects can be tested for simple usability evaluations.

Advances in surgical technology allow physicians to more effectively provide care to their patients. Minimally invasive surgery (MIS) has revolutionized the way a significant number of procedures are performed. Advances in technology have led to the fusion of MIS techniques and robotic devices; however, such systems are currently large and cumbersome. By optimizing a spherical mechanism based on in-vivo data collected during MIS procedures, this paper focuses on a bottom-up approach in developing a new class of surgical robot arms. The spherical mechanism is a rotational manipulator with all axes intersecting at the center of the sphere. Locating the rotational center of the mechanism at the MIS port makes this class of mechanism a suitable candidate for the first two links of a surgical robot for both minimally invasive and open surgery. For optimizing the mechanism structure, the forward and inverse kinematics, as well as the Jacobian matrix, were derived. Using the Jacobian, mechanism isotropy was considered as the performance metric. The dexterous workspace (DWS) is defined as a high dexterity region defined by a right circular cone with a vertex angel of 60/spl deg/ in which 95% of the tool motions are contained based on in-vivo measurements. The extended dexterous workspace (EDWS) is defined as the workspace required to reach the entire abdominal cavity with MIS instruments and defined by a cone with an elliptical cross section created by two orthogonal vertex angels of 60/spl deg/ and 90/spl deg/. Optimization across both the DWS and a superset of the EDWS led to a mechanism configuration with link length angles of 74/spl deg/ and 60/spl deg/ that maximizes kinematic performance and compactness. The workspace of this design covers the entire EDWS and is the optimal design for the next generation of surgical manipulator. By directly applying in-vivo experimental data from MIS in order to optimize the spherical manipulator a design that maximizes performance and minimizes size has been developed. A pair of prototype manipulators is developed based on these results.

Minimally invasive surgery involves a multidimensional series of tasks requiring a synthesis between visual information and the kinematics and dynamics of the surgical tools. Analysis of these sources of information is a key step in mastering MIS, but may also be used to define objective criteria for characterizing surgical performance. The BlueDRAGON is a new system for acquiring the kinematics and dynamics of two endoscopic tools synchronized with the visual view of the surgical scene. It includes two four-bar passive mechanisms equipped with position and force torque sensors for measuring the positions and orientations of the two endoscopic tools along with the forces and torques (F/T) applied by the surgeon's hands. The methodology of decomposing the surgical task is based on a fully connected, 28 finite-states Markov model where each states corresponded to a fundamental tool/tissue interaction based on the tool kinematics and associated with unique F/T signatures. The experimental protocol includes seven MIS tasks performed on an animal model by 30 surgeons at different levels of their residency training including expert surgeons. From the preliminary analysis of these data, the major differences between residents at different skill levels are discussed. Systems like surgical robots or virtual reality simulators that inherently measure the kinematics and dynamics of the surgical tool may benefit from inclusion of the proposed methodology for the analysis of efficacy and objective evaluation of surgical skills during training.