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Multi-Objective Higher Order Polynomial Networks to Model Insertion Force of Bevel-Tip Needles

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  • Hashem Yousefi

    (Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand)

  • Mehdi Fallahnezhad

    (Kavli Institute for Systems Neuroscience/Centre for Biology of Memory, Norwegian University of Science and Technology (NTNU), Trondheim, Norway)

Abstract

Needle insertion has been a very popular minimal invasive surgery method in cancer detection, soft tissue properties recognition and many other surgical operations. Its applications were observed in brain biopsy, prostate brachytherapy and many percutaneous therapies. In this study the authors would like to provide a model of needle force in soft tissue insertion. This model has been developed using higher order polynomial networks. In order to provide a predictive model one-dimensional force sensed on enacting end of bevel-tip needles. The speeds of penetration for quasi-static processes have chosen to be in the range of between 5 mm/min and 300 mm/min. Second and third orders of polynomials employed in the network which contains displacement and speed as their main affecting parameters in the simplified model. Results of fitting functions showed a reliable accuracy in force-displacement graph.

Suggested Citation

  • Hashem Yousefi & Mehdi Fallahnezhad, 2015. "Multi-Objective Higher Order Polynomial Networks to Model Insertion Force of Bevel-Tip Needles," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 5(3), pages 54-70, July.
    • Handle: RePEc:igg:jncr00:v:5:y:2015:i:3:p:54-70
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