Applications of needle insertion with rotating capability in manipulator

Yousefi, Hashem; Ramezanpour, Hosseinali; Rostami, Mostafa

doi:10.1109/icbme.2010.5704994

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…Application of PHONN demonstrates the effect of displacement, velocity as well as correlation of these two parameters in the force model formulation. Other terms such as rotational velocity (Alterovitz, et al, 2005;Yousefi, et al, 2010;Ramezanpour, et al, 2015), accelerations and tapping frequency mentioned by Lagerburg (2006).…”

Section: Discussionmentioning

confidence: 99%

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

Yousefi

Fallahnezhad

2015

International Journal of Natural Computing Research

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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.

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Section: Discussionmentioning

confidence: 99%

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

Yousefi

Fallahnezhad

2015

International Journal of Natural Computing Research

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“… presents methodologies for the measurement of frictional forces and needle geometry effects during the insertion of needles into soft tissues. As the success of medical needle insertion procedures often depends on the success of medial needle guidance to a specific target in soft tissue , in a needle‐insertion system was developed for path‐error correction in a liver environment, using a curved multi‐tubed device. Ultrasound was used as a sensing device to detect the position of the tumour and the orientation of the needle which was inserted into tumour.…”

Section: Introductionmentioning

confidence: 99%

Insertion force in manual and robotic corneal suturing

Yang

Deng

et al. 2011

Robotics Computer Surgery

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Needle Insertion Force Modeling using Genetic Programming Polynomial Higher Order Neural Network

Fallahnezhad

Yousefi

2013

Artificial Higher Order Neural Networks for Modeling and Simulation

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Precise insertion of a medical needle as an end-effecter of a robotic or computer-aided system into biological tissue is an important issue and should be considered in different operations, such as brain biopsy, prostate brachytherapy, and percutaneous therapies. Proper understanding of the whole procedure leads to a better performance by an operator or system. In this chapter, the authors use a 0.98 mm diameter needle with a real-time recording of force, displacement, and velocity of needle through biological tissue during in-vitro insertions. Using constant velocity experiments from 5 mm/min up to 300 mm/min, the data set for the force-displacement graph of insertion was gathered. Tissue deformation with a small puncture and a constant velocity penetration are the two first phases in the needle insertion process. Direct effects of different parameters and their correlations during the process is being modeled using a polynomial neural network. The authors develop different networks in 2nd and 3rd order to model the two first phases of insertion separately. Modeling accuracies were 98% and 86% in phase 1 and 2, respectively.

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Applications of needle insertion with rotating capability in manipulator

Cited by 5 publications

References 7 publications

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

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

Insertion force in manual and robotic corneal suturing

Needle Insertion Force Modeling using Genetic Programming Polynomial Higher Order Neural Network

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