Development and application of a multi-modal task analysis to support intelligent tutoring of complex skills.

Background: Contemporary work in the design and development of intelligent training systems employs task analysis (TA) methods for gathering knowledge that is subsequently encoded into task models. These task models form the basis of intelligent interpretation of student performance within education and training systems. Also referred to as expert models, they represent the optimal way(s) of performing a training task.

Design methodology for a simulator of a robotic surgical system.

Traditional spinal surgery procedures are completed with limited direct visualization. This imposes limitations on the surgeon's ability to place screws into the spine. The Mazor Renaissance robotic system was developed to improve the accuracy of pedicle screw insertion.

A model for predicting the GEARS score from virtual reality surgical simulator metrics.

Background: Surgical education relies heavily upon simulation. Assessment tools include robotic simulator assessments and Global Evaluative Assessment of Robotic Skills (GEARS) metrics, which have been validated. Training programs use GEARS for proficiency testing; however, it requires a trained human evaluator.

A comparative analysis and guide to virtual reality robotic surgical simulators.

Background: Since the US Food and Drug Administration approved robotically assisted surgical devices for human surgery in 2000, the number of surgeries utilizing this innovative technology has risen. In 2015, approximately 650 000 robot-assisted procedures were performed worldwide. Surgeons must be properly trained to safely transition to using such innovative technology.

A Comparison of Robotic Simulation Performance on Basic Virtual Reality Skills: Simulator Subjective Versus Objective Assessment Tools.

Study Objective: To answer the question of whether there is a difference between robotic virtual reality simulator performance assessment and validated human reviewers. Current surgical education relies heavily on simulation. Several assessment tools are available to the trainee, including the actual robotic simulator assessment metrics and the Global Evaluative Assessment of Robotic Skills (GEARS) metrics, both of which have been independently validated.

Robotic surgery simulation validity and usability comparative analysis.

Background: The introduction of simulation into minimally invasive robotic surgery is relatively recent and has seen rapid advancement; therefore, a need exists to develop training curriculums and identify systems that will be most effective at training surgical skills. Several simulators have been introduced to support these aims-the daVinci skills simulator, Mimic dV-Trainer, Surgical Simulated Systems' RoSS, and Simbionix Robotix Mentor. While multiple studies have been conducted to demonstrate the validity of these systems, studies comparing the perceived value of these devices as tools for education and skills are lacking.

Impact of delay on telesurgical performance: study on the robotic simulator dV-Trainer.

Purpose: To determine the impact of communication latency on telesurgical performance using the robotic simulator dV-Trainer®.

Methods: Surgeons were enrolled during three robotic congresses. They were randomly assigned to a delay group (ranging from 100 to 1000 ms).

Crowd-Sourced Assessment of Technical Skills: Differentiating Animate Surgical Skill Through the Wisdom of Crowds.

Background: Objective quantification of surgical skill is imperative as we enter a healthcare environment of quality improvement and performance-based reimbursement. The gold standard tools are infrequently used due to time-intensiveness, cost inefficiency, and lack of standard practices. We hypothesized that valid performance scores of surgical skill can be obtained through crowdsourcing.