Advertisement

VR for Medical Training

  • Robert Riener
  • Matthias Harders

Abstract

There are several benefits of applying VR technology to medicine. VR is more comprehensive than books and cadavers. It is also time and case independent, as the users can train and repeat medical skills at any time they want. Surgeons can practice treatments in extreme situations without taking a risk for the patient, as no patients are directly involved. Procedures are observable and reproducible, and performance can be recorded and used for assessment or evaluation of the treatment. Moreover, augmented information can be displayed to assist the treatment or decision making. Medical applications can benefit from VR in several areas. VR in medicine aims to optimize cost, improve quality of the education and therapy, allow long and efficient training sessions, and increase safety.

The major advantage of VR-based training is that an interactive and engaging setting enables an operator to learn through a first-person experience. Tasks are represented, which would be dangerous, expensive, or even infeasible to undertake in a real setting.

Keywords

Knee Joint Force Feedback Haptic Feedback Training Simulator Haptic Device 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Alhalabi, M.O., Daniulaitis, V., Kawasaki, H., Hori, T.: Medical training simulation for palpation of subsurface tumor using hiro. In: Proceedings of the First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, pp. 623–624. IEEE Computer Society, Washington (2005) CrossRefGoogle Scholar
  2. 2.
    Bachofen, D., Zatonyi, J., Harders, M., Szekely, G., Fruh, P., Thaler, M.: Enhancing the visual realism of hysteroscopy simulation. Stud. Health Technol. Inform. 119, 31–36 (2006) Google Scholar
  3. 3.
    Basdogan, C., Sedef, M., Harders, M., Wesarg, S.: VR-Based simulators for training in minimally invasive surgery. IEEE Comput. Graph. Appl. 27(2), 54–66 (2007). ISI Impact Factor 1.429 CrossRefGoogle Scholar
  4. 4.
    Berkley, J., Turkiyyah, G., Berg, D., Ganter, M., Weghorst, S.: Real-time finite element modeling for surgery simulation: an application to virtual suturing. IEEE Trans. Vis. Comput. Graph. 10(3), 314–325 (2004). doi: 10.1109/TVCG.2004.1272730 CrossRefGoogle Scholar
  5. 5.
    Brett, P.N., Parker, T.J., Harrison, A.J., Thomas, T.A., Carr, A.: Simulation of resistance forces acting on surgical needles. Proc. Inst. Mech. Eng. Part H, J. Eng. Med. 211(4), 335–347 (1997) CrossRefGoogle Scholar
  6. 6.
    Burdea, G., Coiffet, P.: Virtual Reality Technology. Wiley, New York (1993) Google Scholar
  7. 7.
    Burdea, G., Patounakis, G., Popescu, V., Weiss, R.E.: Virtual reality-based training for the diagnosis of prostate cancer. IEEE Trans. Biomed. Eng. 46(10), 1253–1260 (1999). doi: 10.1109/10.790503 CrossRefGoogle Scholar
  8. 8.
    Coles, T., John, N.W., Gould, D.A., Caldwell, D.G.: Haptic palpation for the femoral pulse in virtual interventional radiology. In: Advances in Computer-Human Interactions, 2009. ACHI ’09. Second International Conferences on, pp. 193–198 (2009). doi: 10.1109/ACHI.2009.61 CrossRefGoogle Scholar
  9. 9.
    Coles, T.R., Meglan, D., John, N.W.: The role of haptics in medical training simulators: a survey of the state of the art. IEEE Trans. Haptics 4(1), 51–66 (2011). doi: 10.1109/TOH.2010.19 CrossRefGoogle Scholar
  10. 10.
    Cunningham, R.L., Feldman, P., Feldman, B., Merril, G.L.: Interface device and method for interfacing instruments to vascular access simulation systems (2002). Google Patents. US Patent 6,470,302 Google Scholar
  11. 11.
    Dang, T., Annaswamy, T.M., Srinivasan, M.A.: Development and evaluation of an epidural injection simulator with force feedback for medical training. Med. Meets Virtual Real. 81, 97 (2001) Google Scholar
  12. 12.
    Dupuis, O., Moreau, R., Silveira, R., Pham, M.T., Zentner, A., Cucherat, M., Rudigoz, R.C., Redarce, T.: A new obstetric forceps for the training of junior doctors: a comparison of the spatial dispersion of forceps blade trajectories between junior and senior obstetricians. Am. J. Obstet. Gynecol. 194(6), 1524–1531 (2006). doi: 10.1016/j.ajog.2006.01.013 CrossRefGoogle Scholar
  13. 13.
    Dupuis, O., Moreau, R., Pham, M.T., Redarce, T.: Assessment of forceps blade orientations during their placement using an instrumented childbirth simulator. Int. J. Obstet. Gynaecol. 116(2), 327–333 (2009). doi: 10.1111/j.1471-0528.2008.02004.x CrossRefGoogle Scholar
  14. 14.
    Färber, M., Heller, J., Hummel, F., Gerloff, C., Handels, H.: Virtual reality based training of lumbar punctures using a 6dof haptic device. In: Buzug, T.M., Holz, D., Bongartz, J., Kohl-Bareis, M., Hartmann, U., Weber, S. (eds.) Advances in Medical Engineering. Springer Proceedings in Physics, vol. 114, pp. 236–240. Springer, Berlin (2007). http://dx.doi.org/10.1007/978-3-540-68764-1_39 CrossRefGoogle Scholar
  15. 15.
    Frey, M., Burgkart, R., Regenfelder, F., Riener, R.: Optimised robot-based system for the exploration of elastic joint properties. Med. Biol. Eng. Comput. 42(5), 674–678 (2004) CrossRefGoogle Scholar
  16. 16.
    Frey, M., Hoogen, J., Burgkart, R., Riener, R.: Physical interaction with a virtual knee joint-the 9 dof haptic display of the Munich knee joint simulator. Presence: Teleoperators and Virtual Environments 15(5), 570–587 (2006) CrossRefGoogle Scholar
  17. 17.
    Frey, M., Riener, R., Michas, C., Regenfelder, F., Burgkart, R.: Elastic properties of an intact and acl-ruptured knee joint: measurement, mathematical modelling, and haptic rendering. J. Biomech. 39(8), 1371–1382 (2006) CrossRefGoogle Scholar
  18. 18.
    Gorman, P., Krummel, T., Webster, R., Smith, M., Hutchens, D.: A prototype haptic lumbar puncture simulator. Med. Meets Virtual Real. 70, 106 (2000) Google Scholar
  19. 19.
    Green, P.E., Piantanida, T.A., Hill, J.W., Simon, I.B., Satava, R.M.: Telepresence: dexterous procedures in a virtual operating field. Am. Surg. 57, 192 (1991) Google Scholar
  20. 20.
    Halvorsen, F.H., Elle, O.J., Fosse, E.: Simulators in surgery. Minim. Invasive Ther. Allied Technol. 14(4–5), 214–223 (2005). doi: 10.1080/13645700500243869. http://informahealthcare.com/doi/pdf/10.1080/13645700500243869 CrossRefGoogle Scholar
  21. 21.
    Heng, P.A., Wong, T.T., Yang, R., Chui, Y.P., Xie, Y.M., Leung, K.S., Leung, P.C.: Intelligent inferencing and haptic simulation for Chinese acupuncture learning and training. IEEE Trans. Inf. Technol. Biomed. 10(1), 28–41 (2006) CrossRefGoogle Scholar
  22. 22.
    Langrana, N., Burdea, G., Ladeji, J., Dinsmore, M.: Human performance using virtual reality tumor palpation simulation. Comput. Graph. 21(4), 451–458 (1997) CrossRefGoogle Scholar
  23. 23.
    Liu, A., Tendick, F., Cleary, K., Kaufmann, C.: A survey of surgical simulation: applications, technology, and education. Presence: Teleoperators and Virtual Environments 12(6), 599–614 (2003) CrossRefGoogle Scholar
  24. 24.
    Mayooran, Z., Watterson, L., Withers, P., Line, J., Arnett, W., Horley, R.: Mediseus epidural: full-procedure training simulator for epidural analgesia in labour. In: SimTecT Healthcare Simulation Conference 2006 (2006) Google Scholar
  25. 25.
    Müller, W., Bockholt, U., Lahmer, A., Voss, G., Börner, M.: VRATS—virtual-reality-arthroskopie-trainingssimulator. Radiologe 40(3), 290–294 (2000). doi: 10.1007/s001170050671 CrossRefGoogle Scholar
  26. 26.
    Panchaphongsaphak, B., Burgkart, R., Riener, R.: Three-dimensional touch interface for medical education. IEEE Trans. Inf. Technol. Biomed. 11(3), 251–263 (2007) CrossRefGoogle Scholar
  27. 27.
    Pham, T., Roland, L., Benson, K.A., Webster, R.W., Gallagher, A.G., Haluck, R.S.: Smart tutor: a pilot study of a novel adaptive simulation environment. Stud. Health Technol. Inform. 111, 385–389 (2005) Google Scholar
  28. 28.
    Ra, J.B., Kwon, S.M., Kim, J.K., Yi, J., Kim, K.H., Park, H.W., Kyung, K.U., Kwon, D.S., Kang, H.S., Kwon, S.T., et al.: Spine needle biopsy simulator using visual and force feedback. Comput. Aided Surg. 7(6), 353–363 (2002) CrossRefGoogle Scholar
  29. 29.
    Riener, R., Frey, M., Proll, T., Regenfelder, F., Burgkart, R.: Phantom-based multimodal interactions for medical education and training: the Munich knee joint simulator. IEEE Trans. Inf. Technol. Biomed. 8(2), 208–216 (2004) CrossRefGoogle Scholar
  30. 30.
    Satava, R.M.: Virtual reality surgical simulator: the first steps. Surg. Endosc. 7(3), 203–205 (1993) CrossRefGoogle Scholar
  31. 31.
    Sherman, K.P., Ward, J.W., Wills, D.P., Mohsen, A.M.: A portable virtual environment knee arthroscopy training system with objective scoring. Stud. Health Technol. Inform. 62, 335 (1999) Google Scholar
  32. 32.
    Taffinder, N., Sutton, C., Fishwick, R.J., McManus, I.C., 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. 50, 124–130 (1998) Google Scholar
  33. 33.
    Tokuyasu, T., Kitamura, T., Sakaguchi, G., Komeda, M.: Development of training system for left ventricular plastic surgery. In: Biomedical Engineering, IEEE EMBS Asian-Pacific Conference on, pp. 60–61 (2003). doi: 10.1109/APBME.2003.1302583 CrossRefGoogle Scholar
  34. 34.
    Trifan, A., Stanciu, C.: Computer-based simulator for training in gastrointestinal endoscopy. Rev. Med.-Chir. Soc. Med. Nat. Iasi 111(3), 567–574 (2007) Google Scholar
  35. 35.
    Ullrich, S., Mendoza, J., Ntouba, A., Rossaint, R., Kuhlen, T.: Haptic pulse simulation for virtual palpation. Bildverarb. Med. 10, 187–191 (2008) Google Scholar
  36. 36.
    Vince, J.: Introduction to Virtual Reality. Springer, Berlin (2004) zbMATHCrossRefGoogle Scholar
  37. 37.
    Vining, D.J., Liu, K., Choplin, R.H., Haponik, E.F.: Virtual bronchoscopy: relationships of virtual reality endobronchial simulations to actual bronchoscopy findings. Chest 109(2), 549 (1996) CrossRefGoogle Scholar
  38. 38.
    Wang, Q., Ou, Y., Xu, Y.: A prototype virtual haptic bronchoscope. In: Intelligent Robots and Systems, IEEE/RSJ International Conference on, vol. 2, pp. 1361–1366 (2002). doi: 10.1109/IRDS.2002.1043944 CrossRefGoogle Scholar
  39. 39.
    Zorcolo, A., Gobbetti, E., Pili, P., Tuveri, M., et al.: Catheter insertion simulation with combined visual and haptic feedback. In: Proceedings of the First Phantom Users Research Symposium. Citeseer, Princeton (1999) Google Scholar

Copyright information

© Springer-Verlag London 2012

Authors and Affiliations

  1. 1.Sensory-Motor Systems Lab ETH ZurichUniversity Hospital BalgristZürichSwitzerland
  2. 2.Computer Vision LabETH ZurichZürichSwitzerland

Personalised recommendations