title: Automatic detection and segmentation of robot-assisted surgical motions.
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.
authors: Department of Computer Science, The Johns Hopkins University, Baltimore, MD, USA. hcl@cs.jhu.edu
authors: Henry C
authors: HC
authors: Lin
authors: Izhak
authors: I
authors: Shafran
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