Share Email Print

Proceedings Paper

Recognition of surgical skills using hidden Markov models
Author(s): Stefanie Speidel; Tom Zentek; Gunther Sudra; Tobias Gehrig; Beat Peter Müller-Stich; Carsten Gutt; Rüdiger Dillmann
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Minimally invasive surgery is a highly complex medical discipline and can be regarded as a major breakthrough in surgical technique. A minimally invasive intervention requires enhanced motor skills to deal with difficulties like the complex hand-eye coordination and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality techniques. To recognize and analyze the current situation for context-aware assistance, we need intraoperative sensor data and a model of the intervention. Characteristics of a situation are the performed activity, the used instruments, the surgical objects and the anatomical structures. Important information about the surgical activity can be acquired by recognizing the surgical gesture performed. Surgical gestures in minimally invasive surgery like cutting, knot-tying or suturing are here referred to as surgical skills. We use the motion data from the endoscopic instruments to classify and analyze the performed skill and even use it for skill evaluation in a training scenario. The system uses Hidden Markov Models (HMM) to model and recognize a specific surgical skill like knot-tying or suturing with an average recognition rate of 92%.

Paper Details

Date Published: 13 March 2009
PDF: 8 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 726125 (13 March 2009); doi: 10.1117/12.811140
Show Author Affiliations
Stefanie Speidel, ITEC Univ. Karlsruhe (Germany)
Tom Zentek, ITEC Univ. Karlsruhe (Germany)
Gunther Sudra, ITEC Univ. Karlsruhe (Germany)
Tobias Gehrig, Univ. of Heidelberg (Germany)
Beat Peter Müller-Stich, Univ. of Heidelberg (Germany)
Carsten Gutt, Univ. of Heidelberg (Germany)
Rüdiger Dillmann, ITEC Univ. Karlsruhe (Germany)

Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?