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Proceedings Paper

Immersive training and mentoring for laparoscopic surgery
Author(s): Vasile Nistor; Brian Allen; E. Dutson; P. Faloutsos; G. P. Carman
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Paper Abstract

We describe in this paper a training system for minimally invasive surgery (MIS) that creates an immersive training simulation by recording the pathways of the instruments from an expert surgeon while performing an actual training task. Instrument spatial pathway data is stored and later accessed at the training station in order to visualize the ergonomic experience of the expert surgeon and trainees. Our system is based on tracking the spatial position and orientation of the instruments on the console for both the expert surgeon and the trainee. The technology is the result of recent developments in miniaturized position sensors that can be integrated seamlessly into the MIS instruments without compromising functionality. In order to continuously monitor the positions of laparoscopic tool tips, DC magnetic tracking sensors are used. A hardware-software interface transforms the coordinate data points into instrument pathways, while an intuitive graphic user interface displays the instruments spatial position and orientation for the mentor/trainee, and endoscopic video information. These data are recorded and saved in a database for subsequent immersive training and training performance analysis. We use two 6 DOF DC magnetic trackers with a sensor diameter of just 1.3 mm - small enough for insertion into 4 French catheters, embedded in the shaft of a endoscopic grasper and a needle driver. One sensor is located at the distal end of the shaft while the second sensor is located at the proximal end of the shaft. The placement of these sensors does not impede the functionally of the instrument. Since the sensors are located inside the shaft there are no sealing issues between the valve of the trocar and the instrument. We devised a peg transfer training task in accordance to validated training procedures, and tested our system on its ability to differentiate between the expert surgeon and the novices, based on a set of performance metrics. These performance metrics: motion smoothness, total path length, and time to completion, are derived from the kinematics of the instrument. An affine combination of the above mentioned metrics is provided to give a general score for the training performance. Clear differentiation between the expert surgeons and the novice trainees is visible in the test results. Strictly kinematics based performance metrics can be used to evaluate the training progress of MIS trainees in the context of UCLA - LTS.

Paper Details

Date Published: 11 April 2007
PDF: 11 pages
Proc. SPIE 6528, Nanosensors, Microsensors, and Biosensors and Systems 2007, 65280Q (11 April 2007); doi: 10.1117/12.717199
Show Author Affiliations
Vasile Nistor, Univ. of California, Los Angeles (United States)
Brian Allen, Univ. of California, Los Angeles (United States)
E. Dutson, Univ. of California, Los Angeles (United States)
P. Faloutsos, Univ. of California, Los Angeles (United States)
G. P. Carman, Univ. of California, Los Angeles (United States)

Published in SPIE Proceedings Vol. 6528:
Nanosensors, Microsensors, and Biosensors and Systems 2007
Vijay K. Varadan, Editor(s)

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