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Visualizing Surgical Training Databases

Visualizing Surgical Training Databases: Exploratory Visualization, Data Modeling, and Formative Feedback for Improving Skill Acquisition We present a design study and application of visualization to analyzing multidimensional surgical performance databases collected via emerging surgical robot and simulator technologies. The application visualizes force, position, rotation, and synchronized video data from 300 bimanual laparoscopic surgery tasks performed by more than 50 surgeons. We introduce the design of a new multiple coordinated views framework for exploring these data, along with novel techniques for selecting and filtering multivariate time series data, visualizing animated force plots in conjunction with contextual videos, encoding multivariate bimanual tool trace data within 3D visualizations, and linking visualizations to a database management system via a new generalizable data model. Insights and feedback from an interdisciplinary iterative design process and use case studies support the utility of visualization in this emerging area of data-driven surgical training. Visualizing Surgical Training Databases: Exploratory Visualization, Data Modeling, and Formative Feedback for Improving Skill Acquisition. David Schroeder, Timothy Kowalewski, Lee White, John Carlis, Erlan Santos, Robert Sweet, Thomas S. Lendvay, Troy Reihsen, Daniel F. Keefe. In Press (2012)