By Topic

A cognitive path-guidance-system for minimally invasive surgery

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
O. Weede ; Karlsruhe Institute of Technology (KIT), Institute for Process Control and Robotics, Karlsruhe, Germany ; D. Stein ; N. Gorges ; B. Müller
more authors

The presented path-guidance system is able to learn movements and to predict motion. It shall enhance safe navigation for surgeons in minimally invasive surgery by creating a virtual fixture which holds the end-effector's motion to a desired path and warning the surgeon in a dangerous situation. Surgeons can demonstrate interventions and best practices. The system collects information from surgeon demonstrated trajectories, defined as best practices, and extracts knowledge to provide guidance for other users to carry out the same intervention. Knowledge extraction is achieved through trajectory clustering, maximum likelihood classification and a Markov model to predict states. The fundamental task is to guide a surgeon along a desired trajectory (navigated path) and prevent them entering into zones of risk. The path is not sequential, furcations are permitted and modeled showing alternatives in the ongoing intervention. An evaluation with a pelvitrainer showed good results with over 89% hit rate in predicting the motion.

Published in:

IEEE 8th International Symposium on Intelligent Systems and Informatics

Date of Conference:

10-11 Sept. 2010