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Needle Insertion Force of Biological Soft Tissue for Haptic based Intravenous Injection Simulator

햅틱 기반 정맥주사 시뮬레이터를 위한 생체조직 바늘 삽입력

  • Received : 2011.08.03
  • Accepted : 2011.10.19
  • Published : 2012.02.01

Abstract

Haptics and virtual reality are rapidly growing technologies in medical fields. Physicians and nurses can benefit from medical simulation via training and acquire surgical and clinical techniques. In this paper, the research on needle insertion force of biological tissue for haptic based intravenous injection simulator was carried out. We built the setup for needle insertion (intravenous injection) experiments and performed the experiments on live pigs. The force responses against needle insertion were measured using the experimental setup. In addition, the modeling of needle insertion force was carried out with the experimental results and numerical models via nonlinear least-squares method. The results presented in this paper indicate that the developed models can be applied not only to estimate the force feedback during intravenous injection procedure but also to improve the overall training quality of the medical simulator.

Keywords

References

  1. Cooper, J. B. and Taqueti V. R., "A brief history of the development of mannequin simulator for clinical education and training," Quality and Safety Health Care, Vol. 13, Suppl. 1, pp. i11-i18, 2004.
  2. Scerbo, M. W., Schmidt, E. A. and Bliss, J. P., "Comparison of a Virtual Reality Simulator and Simulated Limbs for Phlebotomy Training," Journal of Infusion Nursing, Vol. 129, No. 4, pp. 214-224, 2006.
  3. Taffinder, N., Sutton, C., Fishwick, R. J., McManus, I. C. and Darzi, A., "Validation of virtual reality to teach and assess psychomotor skills in laparoscopic surgery: results from randomised controlled studies using the MIST VR laparoscopic simulator," Stud. Health. Technol. Inform., Vol. 50, pp. 124-130, 1998.
  4. Tendick, F., Downes, M., Goktekin, T., Cavusoglu, M. C., Feygin, D., Wu, X., Eyal, R., Hegarty, M. and Way, L. W., "A virtual environment testbed for training laparoscopic surgical skills," Presence-Teleoperators and Virtual Environments, Vol. 9, No. 3, pp. 236-255, 2009.
  5. Ahn, B. and Kim, J., "Efficient Soft Tissue Characterization under Large Deformations in Medical Simulations," Int. J. Precision Engineering and Manufacturing, Vol. 10, No. 4, pp. 115-121, 2009. https://doi.org/10.1007/s12541-009-0079-z
  6. Basdogan, C., Ho, C. H. and Srinivasan, M. A., "Virtual environments for medical training: Graphical and haptic simulation of laparoscopic common bile duct exploration," IEEE-ASME Transactions on Mechatronics, Vol. 6, No. 3, pp. 269-285, 2001. https://doi.org/10.1109/3516.951365
  7. Tendick, F., Downes, M., Goktekin, T., Cavusoglu, M. C., Feygin, D., Wu, X., Eyal, R., Hegarty, M. and Way, L. W., "A Virtual Environment Testbed for Training Laparoscopic Surgical Skills," Presence-Teleoperators and Virtual Environments, Vol. 9, No. 3, pp. 236-255, 2000. https://doi.org/10.1162/105474600566772
  8. Cotin, S., Delingette, H. and Ayache, N., "Real Time Elastic Deformations of Soft Tissues for Surgery Simulation," IEEE Transactions on Visualization and Computer Graphics, Vol. 5, No. 1, pp. 62-73, 1999. https://doi.org/10.1109/2945.764872
  9. Fung, Y. C., "Biomechanics Mechanical Properties of Soft Tissues: second edition," Springer-Verlag, 1996.
  10. Miller, K., Chinzei, K., Orssengo, G. and Bednarz, P., "Mechanical properties of brain tissue in vivo: experiment and computer simulation," Journal of Biomechanics, Vol. 33, No. 11, pp. 1369-1376, 2000. https://doi.org/10.1016/S0021-9290(00)00120-2
  11. Schwartz, J. M., Denninger, M., Rancourt, D., Moisan, C. and Laurendeau, D., "Modelling liver tissue properties using a nonlinear visco-elastic model for surgery simulation," Medical Image Analysis, Vol. 9, No. 2, pp. 103-112, 2005. https://doi.org/10.1016/j.media.2004.11.002
  12. Ahn, B. and Kim, J., "Measurement and Characterization of Soft Tissue Behavior with Surface Deformation and Force Response under Large Deformations," Medical Image Analysis, Vol. 14, No. 2, pp. 138-148, 2010. https://doi.org/10.1016/j.media.2009.10.006
  13. Kim, J., Ahn, B., De, S. and Srinivasan, M. A., "An efficient Soft tissue characterization Algorithm from in vivo identation experiments for Medical Simulation," International Journal of Medical Robotics and Computer Assisted Surgery, Vol. 4, No. 3, pp. 277-285, 2008. https://doi.org/10.1002/rcs.209
  14. Kim, J, "Acquisition of biological properties for medical simulation," Journal of the KSME, Vol. 46, No. 11, pp. 48-54, 2006.
  15. Kim, J, "Tools for medical robotic technology-Biometric interaction techniques," Journal of Korea Robotics Society, Vol. 6, No. 1, pp. 13-17, 2009.
  16. Tsai, W., Fung, C., Tsai, S., Jeng, M. and Doong, J., "The Assessment of Stability and Reliability of a Virtual Reality-Based Intravenous Injection Simulator," Computers, Informatics, Nursing, Vol. 26, No. 4, pp. 221-226, 2008. https://doi.org/10.1097/01.NCN.0000304804.46369.5a
  17. Virbac, http://www.virbac.cz/zoletil_guide_cats.html