Exploratory visualization of surgical training databases for improving skill acquisition

David Schroeder, Timothy M Kowalewski, Lee White, John V Carlis, Erlan Santos, Rob Sweet, Thomas S. Lendvay, Daniel F Keefe, Troy Reihsen

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


A new visualization system analyzes multidimensional surgical performance databases of information collected via emerging surgical robot and simulator technologies. In particular, it has visualized force, position, rotation, and synchronized video data from 300 bimanual laparoscopic surgery tasks performed by more than 50 surgeons. To explore data, the system uses a multiple-coordinated-views framework. It provides techniques to select and filter multivariate time series data, visualize animated force plots in conjunction with contextual videos, encode multivariate bimanual tool trace data in 3D visualizations, and link 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.

Original languageEnglish (US)
Article number6212421
Pages (from-to)71-81
Number of pages11
JournalIEEE Computer Graphics and Applications
Issue number6
StatePublished - 2012

Bibliographical note

Funding Information:
The University of Minnesota Digital Technology Center’s Digital Technologies Initiative and Washington Technology Center Research Technology Development grant RTD11 UW SB01 supported this research.


  • computer graphics
  • laparoscopic surgery
  • surgical performance
  • visualization


Dive into the research topics of 'Exploratory visualization of surgical training databases for improving skill acquisition'. Together they form a unique fingerprint.

Cite this