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Objective skill evaluation for laparoscopic training based on motion analysis

journal contribution
posted on 2015-05-21, 13:03 authored by Zhuohua Lin, M. Uemura, Massimiliano ZeccaMassimiliano Zecca, Salvatore Sessa, Hiroyuki Ishii, M. Tomikawa, M. Hashizume, Atsuo Takanishi
Performing laparoscopic surgery requires several skills, which have never been required for conventional open surgery. Surgeons experience difficulties in learning and mastering these techniques. Various training methods and metrics have been developed to assess and improve surgeon's operative abilities. While these training metrics are currently widely being used, skill evaluation methods are still far from being objective in the regular laparoscopic skill education. This study proposes a methodology of defining a processing model that objectively evaluates surgical movement performance in the routine laparoscopic training course. Our approach is based on the analysis of kinematic data describing the movements of surgeon's upper limbs. An ultraminiaturized wearable motion capture system (Waseda Bioinstrumentation system WB-3), therefore, has been developed to measure and analyze these movements. The data processing model was trained by using the subjects' motion features acquired from the WB-3 system and further validated to classify the expertise levels of the subjects with different laparoscopic experience. Experimental results show that the proposed methodology can be efficiently used both for quantitative assessment of surgical movement performance, and for the discrimination between expert surgeons and novices.

Funding

The authors would also like to express their gratitude to Okino Industries Ltd., Japan, Robotech Ltd., SolidWorks Corp., Dyden, for their support to the research.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Volume

60

Issue

4

Pages

977 - 985 (9)

Citation

LIN, Z. ... et al, 2013. Objective skill evaluation for laparoscopic training based on motion analysis. IEEE Transactions on Biomedical Engineering, 60 (4), pp. 977 - 985.

Publisher

© IEEE

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2013

Notes

This article is closed access.

ISSN

0018-9294

Language

  • en