Application of self organizing Kohonen map to detection of surgeon motions during endoscopic surgery

Segmentation of the surgeonpsilas hand movements during the surgery into more primitive parts and recognition of those parts using Kohonen map is discussed in present paper. Main advantages of the proposed approach are that it allows to take into account dynamical characteristics of the hand movemen...

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Hauptverfasser:	Petlenkov, E., Nomm, S., Vain, J., Miyawaki, F.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Artificial neural networks Humans Motion segmentation Robot kinematics Robots Surgery Switches
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creator	Petlenkov, E. Nomm, S. Vain, J. Miyawaki, F.
description	Segmentation of the surgeonpsilas hand movements during the surgery into more primitive parts and recognition of those parts using Kohonen map is discussed in present paper. Main advantages of the proposed approach are that it allows to take into account dynamical characteristics of the hand movements and exclude probability of human error in building etalon segmentation. Ability to recognize current action of the surgeon has a crucial importance in developing a robot able to assist surgeon during the endoscopic surgical operation. One of the possible ways is to predefine a set of possible surgeonpsilas actions and provide a recognition algorithm explored in the framework of present contribution.
doi_str_mv	10.1109/IJCNN.2008.4634193
format	Conference Proceeding
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ispartof	2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008, Vol.10, p.2806-2811
issn	2161-4393 1522-4899 2161-4407
language	eng
recordid	cdi_proquest_miscellaneous_34516557
source	IEEE Electronic Library (IEL) Conference Proceedings
subjects	Artificial neural networks Humans Motion segmentation Robot kinematics Robots Surgery Switches
title	Application of self organizing Kohonen map to detection of surgeon motions during endoscopic surgery
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