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Large Deformation Characterization of Mouse Oocyte Cell Under Needle Injection Experiment | ||
| AUT Journal of Modeling and Simulation | ||
| مقاله 3، دوره 44، شماره 1، تیر 2012، صفحه 21-25 اصل مقاله (205.53 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/miscj.2012.22 | ||
| نویسندگان | ||
| Ali A. Abbasi* 1؛ M.T. Ahmadian2 | ||
| 1Corresponding Author, School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran, Email: Ali.eng.edu@gmail.com. | ||
| 2Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran. | ||
| چکیده | ||
| In order to better understand the mechanical properties of biological cells, characterization and investigation of their material behavior is necessary. In this paper hyperelastic Neo-Hookean material is used to characterize the mechanical properties of mouse oocyte cell. It has been assumed that the cell behaves as continuous, isotropic, nonlinear and homogenous material for modeling. Then, by matching the experimental data with finite element (FE) simulation result and using the Levenberg–Marquardt optimization algorithm, the nonlinear hyperelastic model parameters have been extracted. Experimental data of mouse oocyte captured from literatures. Advantage of the developed model is that it can be used to calculate accurate reaction force on surgical instrument or it can be used to compute deformation or force in virtual reality based medical simulations. | ||
| کلیدواژهها | ||
| Biological cells؛ Levenberg–Marquardt optimization algorithm؛ Inverse finite element؛ hyperelastic material | ||
| عنوان مقاله [English] | ||
| Large Deformation Characterization of Mouse Oocyte Cell Under Needle Injection Experiment | ||
| چکیده [English] | ||
| In order to better understand the mechanical properties of biological cells, characterization and investigation of their material behavior is necessary. In this paper hyperelastic Neo-Hookean material is used to characterize the mechanical properties of mouse oocyte cell. It has been assumed that the cell behaves as continuous, isotropic, nonlinear and homogenous material for modeling. Then, by matching the experimental data with finite element (FE) simulation result and using the Levenberg–Marquardt optimization algorithm, the nonlinear hyperelastic model parameters have been extracted. Experimental data of mouse oocyte captured from literatures. Advantage of the developed model is that it can be used to calculate accurate reaction force on surgical instrument or it can be used to compute deformation or force in virtual reality based medical simulations. | ||
| کلیدواژهها [English] | ||
| Biological cells, Levenberg–Marquardt optimization algorithm, Inverse finite element, hyperelastic material | ||
| مراجع | ||
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[1] C.T. Lim, E.H. Zhou, and S.T. Quek, "Mechanical models for living cells—a review,” Journal of Biomechanics, vol. 39, pp.195–216. 2006. [2] Y. Tan, D. Sun, W. Huang, and S. Han Cheng, "Characterizing Mechanical Properties of Biological Cells by Microinjection,” IEEE Transactions on Nanobioscience, Vol. 9, No. 3, September 2010. [3] F.P.T. Baaijens, W.R. Trickey, T.A. Laursen, and F. Guilak, "Large deformation finite element analysis of micropipette aspiration to determine the mechanical properties of the chondrocyte". Annals of Biomedical Engineering, vol.33, No.4, pp. 494–501. 2005. [4] Y. Tan, D. Sun, and W. Huang, “Mechanical modeling of red blood cells during optical stretching,” J. Biomech. Eng.-Trans. ASME, vol. 132, pp. 044504, 2010. [5] Y. Kim, J. H. Shin, and J. Kim, “Atomic Force Microscopy Probing for Biomechanical Characterization of Living Cells,” Proceedings of the 2nd Biennial IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics Scottsdale, AZ, USA, October 19-22, 2008. [6] M.T. Ahmadian, G.R. Vossoughi, A.A. Abbasi, P. Raeissi,“Modeling Of Cell Deformation Under External Force Using Artificial Neural Network” , Proceedings of the ASME 2010 International Mechanical Engineering Congress & Exposition, November 12-18, 2010, Vancouver, British Columbia, Canada. [7] M.T. Ahmadian, G.R. Vossoughi, A.A. Abbasi, P. Raeissi, “Cell Deformation Modeling Under External Force Using Artificial Neural Network” Journal of Solid Mechanics Vol. 2, No. 2, pp 190-198. 2010. [8] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Deformation Prediction Of Mouse Embryos In Cell Injection Experiment By A Feed forward Artificial Neural Network” Proceedings of the ASME International Design Engineering Technical Conferences &Computers and Information in Engineering Conference, August 29-31, 2011, Washington, DC, USA. [9] A. A. Abbasi, H. Sayyaadi, G.R. Vossoughi, “Sensitivity Analysis Of Mouse Embryos In Needle Injection Experiment Using Artificial Neural Network”, 2nd International Conference on Future Information Technology (ICFIT 2011), 16-18 September 2011, Singapore.
[10] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Deformation Prediction By A Feed forward Artificial Neural Network during mouse embryo micromanipulation” Animal cells and systems, Vol. 16, No. 2, pp.121-126,2012. [11] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Application Of Adaptive Neural Fuzzy Inference Technique For Biological Cell Modeling –Part A:Deformation Prediction” 2nd International Conference on Future Information Technology (ICFIT 2011), 16-18 September 2011, Singapore. [12] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Application of Adaptive Neural Fuzzy Inference Technique for Biological Cell Modeling –Part B: Prediction of External Applied Force”, 2nd International Conference on Future Information Technology (ICFIT 2011), 16-18 September 2011, Singapore. [13] L.G. Alexopoulos, M.A. Haider, T.P. Vail, and F. Guilak, “Alterations in the mechanical properties of the human chondrocyte pericellular matrix with osteoarthritis”. Journal of Biomechanical Engineering 125 (3), 323–333, 2003. [14] E.H. Zhou, C.T. Lim, and S.T. Quek, “Finite element simulation of the micropipette aspiration of a living cell undergoing large viscoelastic deformation” Mechanics of Advanced Materials and Structures, vol. 12, No. 6, pp. 501–512, 2005. [15] T. Boudou, J. Ohayon, Y. Arntz, G. Finet, C. Picart, P. Tracqui,. An extended modeling of the micropipette aspiration experiment for the characterization of the Young’s modulus and Poisson’s ratio of adherent thin biological samples: numerical and experimental studies. Journal of Biomechanics, vol. 39 No. 9, pp.1677–1685, 2006. [16] M. Flückiger, “Cell Membrane Mechanical Modeling for Microrobotic Cell Manipulation”, Diploma Thesis, ETHZ Swiss Federal Institute of Technology, Zurich, WS03/04, 2004. [17] Y. Sun, K.T. Wan, K.P. Roberts, J.C. Bischof, and B.J. Nelson, “Mechanical Property Characterization of Mouse Zona Pellucida” IEEE Transactions on Nanobioscience, vol. 2, pp.279-286, 2003. [18] A. Bummo and J. Kim, “an Efficient Soft Tissue Characterization Method for Haptic Rendering of Soft Tissue Deformation in Medical Simulation”, Frontiers in the Convergence of Bioscience and Information Technologies 2007.IEEE. [19] Abaqus/CAE user’s manual, Version 6.9, Inc., Providence, RI, USA, 2009. [20] W.H. Press, S.A. Teukolsky, W.T. Vetterling and B.P. Flannery, Numerical recipes in C++. The art of scientific computing, second ed. Cambridge University Press, 1992. [21] A. A. Abbasi, “Modeling of biological cells with applications to the design of a nano-micro gripper used in cell manipulation”, M.S. thesis, Sharif University of technology, Tehran, Iran, 2011. [22] E. Samur, M. Sedef, C. Basdogan, L. Avtan and O. Duzgun, “A robotic indenter for minimally invasive measurement and characterization of soft tissue response”, Medical Image Analysis vol. 11, pp. 361–373, 2007. | ||
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