Document Type
Report
Abstract
Robotic surgical systems such as Intuitive Surgical's da Vinci system provide a rich source of motion and video data from surgical procedures. In principle, this data can be used to evaluate surgical skill, provide surgical training feedback, or document essential aspects of a procedure. If processed online, the data can be used to provide context-specific information or motion enhancements to the surgeon. However, in every case, the key step is to relate recorded motion data to a model of the procedure being performed. This paper examines our progress at developing techniques for "parsing" raw motion data from a surgical task into a labelled sequence of surgical gestures. Our current techniques have achieved >90% fully automated recognition rates on 15 datasets.
Publication Date
2007
Recommended Citation
Lin, Henry C., "Automatic Detection and Segmentation of Robot-Assisted Surgical Motions" (2007). Link Foundation Modeling, Simulation and Training Fellowship Reports. 12.
https://repository.fit.edu/link_modeling/12
Standard cover form for report
Comments
Link Foundation Fellowship for the years 2006-2007.