UIUX Design VR Training for Robotic Operating Room
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The training scenario involves interacting with a virtual surgeon and a virtual non-sterile staff member to troubleshoot an instrument arm by attempting to restart the system, using a special tool to open the instrument’s jaws, removing the instrument, stowing the arm, and disabling it.
Da Vinci Robotic OR
An advanced robotic platform designed to enhance the capabilities of surgeons performing minimally invasive surgeries. The system includes a set of robotic arms, a high-definition 3D camera, and a surgeon's console that allows for precise control of surgical instruments. This technology offers greater dexterity, precision, and control than traditional laparoscopic surgery, allowing surgeons to perform complex procedures through small incisions with improved accuracy and reduced patient recovery time. The Da Vinci system is widely used across various specialties, including urology, gynecology, cardiothoracic, and general surgery, providing patients with the benefits of shorter hospital stays, less pain, and faster recovery.
To accomplish the training scenario provided by INTUITIVE surgical, the VR training application designed in this article includes 24 steps that require various actions of the user. It is important to note that the application uses dialog buttons for conversing with the virtual agents. For each step, the application uses an interaction cue to guide the user through the troubleshooting scenario. Each cue employs subtle verbal instructions from one of the virtual agents for feedforward and integrated visual animations as perceived affordances. All the cues are scenario-triggered.
Training Requirements
Different Tasks
The application’s training scenario involves interacting with a virtual operating room (OR) team to troubleshoot the surgical robot after an instrument failure. To accomplish the scenario, the application requires the user to complete a variety of steps, including moving about the OR (i.e., travel via real walking), selecting dialog options and picking up tools (i.e., selection via virtual hand), and interacting with instruments and the surgical robot(i.e., manipulation via virtual hand). The scenario involves a total of 24 steps, including 4 travel tasks, 13 selection tasks, and 7 manipulation tasks.
User Research Conducted to Evaluate the Training System
For each metric, I conducted a three-way (session, purpose, timing), mixed (session and purpose within, timing between), repeated measures analysis of variance (RM-ANOVA) at a 95% confidence level. The Shapiro-Wilk test of normality was used to ensure results were approximately normally distributed. Degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity when Mauchly’s test of sphericity indicated that the assumption of sphericity had been violated. Bonferroni corrections and post hoc tests were used to correct for Type I errors in the repeated measures and to identify significantly different conditions when a significant main effect was found.
