Part of the book series:Advances in Intelligent Systems and Computing ((AISC,volume 302))
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Abstract
In recent years percutaneous treatments for cancer have won momentum in the medical field. With it new needle insertion robots appeared to overcome the difficulties associated with needle insertion into soft tissue. At first, the main focus was to achieve high needle placement accuracy, however, the focus nowadays has shifted toward needle steering and patient specific needle tissue interaction. In this paper we present a classification method to detect the type of tissue being punctured in real time. The purpose of the proposed method is to detect particular events that can be used in a situational awareness agent. First, we will introduce the methodology to create the statistical models used for classification, next, we prove the feasibility of the proposed classification method with experimental results and show that the proposed method hit a target even when tissue is deformed by analyzing needle insertion force patterns.
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Authors and Affiliations
Graduate School of Advanced Science and Engineering, Waseda University, Tokyo, Japan
Inko Elgezua, Sangha Song & Yo Kobayashi
Faculty of Science and Engineering, Waseda University, Tokyo, Japan
Masakatsu G. Fujie
- Inko Elgezua
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- Sangha Song
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- Yo Kobayashi
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- Masakatsu G. Fujie
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Correspondence toInko Elgezua.
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Editors and Affiliations
Information Engineering, University of Padua, Padua, Italy
Emanuele Menegatti
Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
Nathan Michael
Fachbereich Informatik, Technische Universität Kaiserslautern Arbeitsgruppe Robotersysteme, Kaiserslautern, Germany
Karsten Berns
Integrated Information Technology, Aoyama Gakuin University, Tokyo, Japan
Hiroaki Yamaguchi
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Elgezua, I., Song, S., Kobayashi, Y., Fujie, M.G. (2016). Online Event Classification for Liver Needle Insertion Based on Force Patterns. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_83
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