A Review of Simulators with Haptic Devices for Medical Training

  • David Escobar-Castillejos
  • Julieta Noguez
  • Luis Neri
  • Alejandra Magana
  • Bedrich Benes
Education & Training
Part of the following topical collections:
  1. Education & Training

Abstract

Medical procedures often involve the use of the tactile sense to manipulate organs or tissues by using special tools. Doctors require extensive preparation in order to perform them successfully; for example, research shows that a minimum of 750 operations are needed to acquire sufficient experience to perform medical procedures correctly. Haptic devices have become an important training alternative and they have been considered to improve medical training because they let users interact with virtual environments by adding the sense of touch to the simulation. Previous articles in the field state that haptic devices enhance the learning of surgeons compared to current training environments used in medical schools (corpses, animals, or synthetic skin and organs). Consequently, virtual environments use haptic devices to improve realism. The goal of this paper is to provide a state of the art review of recent medical simulators that use haptic devices. In particular we focus on stitching, palpation, dental procedures, endoscopy, laparoscopy, and orthopaedics. These simulators are reviewed and compared from the viewpoint of used technology, the number of degrees of freedom, degrees of force feedback, perceived realism, immersion, and feedback provided to the user. In the conclusion, several observations per area and suggestions for future work are provided.

Keywords

E-learning Medical training Haptic devices 3D simulators Training 

References

  1. 1.
    Vanlehn, K., The Behavior of Tutoring Systems. Int. J. Artif. Intell. Educ. 16(3):227–265.Google Scholar
  2. 2.
    Gazibara, T, Marusic, V., Maric, G., Zaric, M., Vujcic, I., Kisic-Tepavcevic, D., Maksimovic, J., Maksimovic, N., Denic, L. M., Grujicic, S. S., Pekmezovic, T., Grgurevic, A., Introducing E-learning in Epidemiology Course for Undergraduate Medical Students at the Faculty of Medicine, University of Belgrade: A Pilot Study. J. Med. Syst. 40(3):1–12 , 2015.Google Scholar
  3. 3.
    Ito, M., Sugito, M., Kobayashi, A., Nishizawa, Y., Tsunoda, Y., Saito, N., Influence of learning curve on short-term results after laparoscopic resection for rectal cancer. Surg. Endosc. 23(2):403–408, 2009.CrossRefPubMedGoogle Scholar
  4. 4.
    Tseng, J. F., Pisters, P. W., Lee, J. E., Wang, H., Gómez, H. F., Sun, C. C., Evans, D. B., The learning curve in pancreatic surgery. Surgery 141(4):456–463, 2007.CrossRefPubMedGoogle Scholar
  5. 5.
    Vickers, A.J., Savage, C.J., Hruza, M., Tuerk, I., Koenig, P., Martínez-Piñeiro, L., Janetschek, G., Guillonneau, B., The surgical learning curve for laparascopic compared to open radical prostatectomy: a retrospective cohort study. Lancet Oncol. 10(5):475–480, 2009.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Lau, F., and Bates, J., A review of e-learning practices for undergraduate medical education. J. Med. Syst. 28(1):71–87 , 2004.CrossRefPubMedGoogle Scholar
  7. 7.
    Juanes, J. A., and Ruisoto, P., Computer applications in health science education. J. Med. Syst. 39(9):1–5, 2015.CrossRefGoogle Scholar
  8. 8.
    Secin, F. P., Savage, C., Abbou, C., de La Taille, A., Salomon, L., Rassweiler, J., Hruza, M., Rozet, F., Cathelineau, X., Janetschek, G., Nassar, F., Turk, I., Vanni, A. J., Gill, I. S., Koenig, P., Kaouk, J. H., Martinez Pineiro, L., Pansadoro, V., Emiliozzi, P., Bjartell, A., Jiborn, T., Eden, C., Richards, A.J., Van Velthoven, R., Stolzenburg, J.-U., Rabenalt, R., Su, L.-M., Pavlovich, C. P., Levinson, A.W., Touijer, K.A., Vickers, A., Guillonneau, B., The learning curve for laparoscopic radical prostatectomy: an international multicenter study. J. Urol. 184(6):2291–2296 , 2010.CrossRefPubMedPubMedCentralGoogle 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. Haptic 4(1):51–66, 2011.CrossRefGoogle Scholar
  10. 10.
    Cotin, S., Delingette, H., Ayache, N., Real-Time Elastic Deformations of Soft Tissues for Surgery Simulation. IEEE Trans. Vis. Comput. Graph. 5(1):62–73, 1999.CrossRefGoogle Scholar
  11. 11.
    Brown, J., Sorkina, S., Latombea, J. -C., Montgomery, K., Stephanides, M., Algorithmic Tools for Real-Time Microsurgery Simulation. Med. Image Anal. 6(3):289–300, 2002.CrossRefPubMedGoogle Scholar
  12. 12.
    Immersion Medical, Medical Solutions, [accessed Oct-15-2014]. http://www.immersion.com/markets/medical/solutions/index.html
  13. 13.
    Mentice, About us, [accessed Oct-15-2014]. http://www.mentice.com/about-us/
  14. 14.
    ReachIn Technologies, About ReachIn Technologies, [accessed Oct-15-2014]. http://www.reachin.se/companyinfo/
  15. 15.
    Science, Surgical, About us, [accessed Oct-15-2014]. http://www.surgical-science.com/surgical-science/about-us/
  16. 16.
    Simbionix, GI Mentor, [accessed Jan-18-2016]. http://simbionix.com/simulators/gi-mentor/
  17. 17.
    CAE Healthcare, CAE Healthcare, [accessed Feb-15-2015]. http://www.caehealthcare.com/eng/
  18. 18.
    Basdogan, C., and Srinivasan, M.A.: Haptic Rendering in Virtual Environments. In: Handbook of Virtual Environments, 2002, pp. 117–134Google Scholar
  19. 19.
    Massie, T.H., Design of a Three Degree of Freedom Force-Reflecting Haptic Interface, Ph.D. thesis, 1993.Google Scholar
  20. 20.
    Van der Linde, R.Q., Lammertse, P., Frederiksen, E., Ruiter, B.: The hapticmaster, a new high-performance haptic interface. In: Proc. Euro-haptics (2002), pp. 1–5Google Scholar
  21. 21.
    Basdogan, C., De, S., Kim, J., Muniyandi, M., Kim, H., Srinivasan, M. A., Haptics in minimally invasive surgical simulation. IEEE Comput. Graph. Appl. 24(2):56–64, 2004.CrossRefPubMedGoogle Scholar
  22. 22.
    Marshall, P., Payandeh, S., Dill, J.: A study on haptic rendering in a simulated surgical training environment. In: 14th symposium on haptic interfaces for virtual environment and teleoperator systems, 2006, pp. 241–247Google Scholar
  23. 23.
    Jia, S., and Pan, Z.: A preliminary study of suture simulation in virtual surgery. In: International conference on audio language and image processing (ICALIP), 2010, pp. 1340–1345Google Scholar
  24. 24.
    Brown, J., Latombe, J.-C., Montgomery, K., Real-time knot-tying simulation. Vis. Comput. 20(2-3): 165–179, 2004.CrossRefGoogle Scholar
  25. 25.
    Payandeh, S., and Shi, F., Interactive multi-modal suturing. Virtual Reality 14(4):241–253, 2010.CrossRefGoogle Scholar
  26. 26.
    Ricardez, E., Noguez, J., Neri, L., Munoz-Gomez, L., Escobar-Castillejos, D.: SutureHap : A suture simulator with haptic feedback. In: Workshop on virtual reality interaction and physical simulation VRIPHYS, 2014, pp. 79–86Google Scholar
  27. 27.
    Choi, K.-S., Chan, S.-H., Pang, W.-M., Virtual suturing simulation based on commodity physics engine for medical learning. J. Med. Syst. 36(3):1781–1793, 2012.CrossRefPubMedGoogle Scholar
  28. 28.
    Salisbury, K., Conti, F., Barbagli, F., Haptic rendering: introductory concepts. IEEE Comput. Graph. Appl. 24(2):24–32, 2004.CrossRefPubMedGoogle Scholar
  29. 29.
    Min, L., Faragasso, A., Konstantinova, J., Aminzadeh, V., Seneviratne, L., Dasgupta, P., Althoefer, K.: A novel tumor localization method using haptic palpation based on soft tissue probing data. In: IEEE international conference on robotics and automation (ICRA), 2014, pp. 4188–4193Google Scholar
  30. 30.
    Ullrich, S., and Kuhlen, T., Haptic palpation for medical simulation in virtual environments. IEEE Trans. Vis. Comput. Graph. 18(4):617–625, 2012.CrossRefPubMedGoogle Scholar
  31. 31.
    Coumans, E.: Bullet physics library, [accessed April-15-2015]. http://bulletphysics.org/wordpress/
  32. 32.
    Coles, T., John, N., Gould, D., Caldwell, D., Integrating haptics with augmented reality in a femoral palpation and needle insertion training simulation. IEEE Trans. Haptic 4(3):199–209, 2011.CrossRefGoogle Scholar
  33. 33.
    Phantom Head Dental Ltd, Phantom Head, [accessed Oct-15-2014]. http://www.phantomhead.com/
  34. 34.
    Tse, B., Harwin, W., Barrow, A., Quinn, B., San Diego, J., Cox, M.: Design and development of a haptic dental training system - hapTEL. In: Vol. 6192 of Lecture Notes in Computer Science - Haptics: Generating and Perceiving Tangible Sensations, Springer Berlin Heidelberg, pp. 101–108 (2010)Google Scholar
  35. 35.
    Si, H., Tetgen, [accessed Oct-15-2014]. http://wias-berlin.de/software/tetgen/
  36. 36.
    Chen, X., Lin, Y., Wang, C., Shen, G., Wang, X.: A virtual training system using a force feedback haptic device for oral implantology. In: Transactions on edutainment VIII, Springer Berlin Heidelberg, 2012, pp. 232–240Google Scholar
  37. 37.
    Kosuki, Y., Okada, Y., 3D visual component based development system for medical training systems supporting haptic devices and their collaborative environments. In: Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), 2012, pp. 687–692Google Scholar
  38. 38.
    Hui, Z., and Dang-xiao, W.: Soft tissue simulation with bimanual force feedback. In: International conference on audio language and image processing (ICALIP), 2010, pp. 903–907Google Scholar
  39. 39.
    Yanng, B., Intelligent learning system based on HMM model, 2011 Intl. Symposium on Knowledge Acquisition and Modeling (KAM),560–564, 2011.Google Scholar
  40. 40.
    Okada, Y., and Tanaka, Y.: Intelligentbox: A constructive visual software development system for interactive 3D graphic applications. In: Proceedings computer animation, 1995, pp. 114–125, 213Google Scholar
  41. 41.
    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.CrossRefPubMedGoogle Scholar
  42. 42.
    Wang, D., Zhang, Y., Hou, J., Wang, Y., Lv, P., Chen, Y., Zhao, H., iDental: A haptic-based dental simulator and its preliminary user evaluation. IEEE Trans. Haptic 5(4):332–343, 2012.CrossRefGoogle Scholar
  43. 43.
    SensAble, Ghost SDK, [accessed April-10-2015]. http://www.dentsable.com/support-ghost-sdk.htm
  44. 44.
    Rodwin, M.A., Chang, H.J., Ozaeta, M.M., Omar, R., Malpractice premiums in massachusetts, a high-risk state: 1975 to 2005. Health Aff. 27(3):835–844, 2008.CrossRefGoogle Scholar
  45. 45.
    Stone, S., and Bernstein, M., Prospective error recording in surgery: an analysis of 1108 elective neurosurgical cases. Neurosurgery 60(6):1075–1080, 2007.CrossRefPubMedGoogle Scholar
  46. 46.
    Delorme, S., Laroche, D., DiRaddo, R., Del Maestro, R.F., NeuroTouch: a physics-based virtual simulator for cranial microneurosurgery training. Neurosurgery 71:32–42, 2012.PubMedGoogle Scholar
  47. 47.
    Jiang, D., Hovdebo, J., Cabral, A., Mora, V., Delorme, S., Endoscopic third ventriculostomy on a microneurosurgery simulator. SIMULATION: Transactions of The Society for Modeling and Simulation International 89(12):1442–1449, 2013.CrossRefGoogle Scholar
  48. 48.
    Neubauer, A., Wolfsberger, S., Forster, M. -T., Mroz, L., Wegenkittl, R., Buhler, K., Advanced virtual endoscopic pituitary surgery. IEEE Trans. Vis. Comput. Graph. 11(5):497–507, 2005.CrossRefPubMedGoogle Scholar
  49. 49.
    Perez-Gutierrez, B., Martinez, D.M., Rojas, O.E., Endoscopic endonasal haptic surgery simulator prototype: A rigid endoscope model, 2010 IEEE Virtual Reality Conference (VR), 2010Google Scholar
  50. 50.
    Bioingenium Research Group, Nukak3D, [accessed Oct-15-2014]. http://nukak3d.sourceforge.net/index.php
  51. 51.
    Punak, S., Kurenov, S., Cance, W.: Virtual interrupted suturing exercise with the Endo stitch suturing device. In: Advances in visual computing, Springer Berlin Heidelberg, 2011, pp. 55–63Google Scholar
  52. 52.
    Spillmann, J., and Teschner, M.: CoRdE: Cosserat Rod elements for the dynamic simulation of one-dimensional elastic objects. In: Eurographics/ACM SIGGRAPH symposium on computer animation, 2007, pp. 1–10Google Scholar
  53. 53.
    Park, C.H., Wilson, K.L., Howard, A.M.: Examining the learning effects of a low-cost haptic-based virtual reality simulator on laparoscopic cholecystectomy. In: Proceedings of the 26th IEEE international symposium on computer-based medical systems, 2013, pp. 233–238Google Scholar
  54. 54.
    Gaudina, M., Zappi, V., Bellanti, E., Vercelli, G.: eLaparo4D: A step towards a physical training space for virtual video laparoscopic surgery. In: IEEE seventh international conference on complex, intelligent, and software intensive systems, 2013, pp. 611–616Google Scholar
  55. 55.
    Unity Technologies, Unity - Game engine, tools, and multiplatform, [accessed Jan-18-2015]. https://unity3d.com/es/unity
  56. 56.
    Blender Foundation, Blender, [accessed Oct-15-2014]. http://www.blender.org/
  57. 57.
    De Paolis, L.T.: Serious game for laparoscopic suturing training. In: IEEE sixth international conference on complex, intelligent, and software intensive systems (CISIS), 2012, pp. 481–485Google Scholar
  58. 58.
    Torus Knot Software Ltd, Ogre3D, [accessed Oct-15–2014]. http://www.ogre3d.org/
  59. 59.
    Halic, T., and De, S.: Lightweight bleeding and smoke effect for surgical simulators. In: IEEE virtual reality conference (VR), 2010, pp. 271–272Google Scholar
  60. 60.
    De, S., Ahn, W., Lee, D.Y., Jones, D.B.: Novel virtual lap-band simulator could promote patient safety. In: Medicine meets virtual reality 16, 2008, pp. 98–100Google Scholar
  61. 61.
    Hernansanz, A., Zerbato, D., Gasperotti, L., Scandola, M., Fiorini, P., Casals, A.: Improving the development of surgical skills with virtual fixtures in simulation. In: Information processing in computer-assisted interventions, Springer Berlin Heidelberg, 2012, pp. 157–166Google Scholar
  62. 62.
    Rasmussen, J., and Member, S., Skills, Rules, and Knowledge; Signals, Signs, and Symbols, and Other Distinctions in Human Performance Models. IEEE Trans. Syst. Man Cybern. 13(3):257–266, 1983.CrossRefGoogle Scholar
  63. 63.
    Zerbato, D., Baschirotto, D., Baschirotto, D., Botturi, D., Fiorini, P., GPU-based physical cut in interactive haptic simulations. Int. J. Comput. Assist. Radiol. Surg. 6(2):265–72, 2011.CrossRefPubMedGoogle Scholar
  64. 64.
    Chen, Y., and He, X.: Haptic simulation of bone drilling based on hybrid 3d part representation. In: 2013 IEEE international conference on computational intelligence and virtual environments for measurement systems and applications (CIVEMSA), 2013, pp. 78-81Google Scholar
  65. 65.
    Cecil, J., Ramanathan, P., Rahneshin, V., Prakash, A., Pirela-Cruz, M.: Collaborative virtual environments for orthopedic surgery. In: IEEE international conference on automation science and engineering (CASE), 2013, pp. 133-137Google Scholar
  66. 66.
    Ni, D., Chan, W. -Y., Qin, J., Chui, Y. -P., Qu, I., Ho, S., Heng, P. -A., A virtual reality simulator for ultrasound-guided biopsy training. IEEE Comput. Graph. Appl. 31(2):36–48, 2011.CrossRefGoogle Scholar
  67. 67.
    Selmi, S.-Y., Fiard, G., Promayon, E., Vadcard, L., Troccaz, J.: A virtual reality simulator combining a learning environment and clinical case database for image-guided prostate biopsy. In: IEEE 26th international symposium on computer-based medical systems (CBMS), 2013, pp. 179-184Google Scholar
  68. 68.
    TIMC-IMAG laboratory, Computer Assisted Medical Intervention Tool Kit, [accessed Jan-01-2016]. http://camitk.imag.fr/
  69. 69.
    Yi, N., Xiao-jun, G., Xiao-ru, L., Xiang-feng, X., Wanjun, M.: The implementation of haptic interaction in virtual surgery. In: International conference on electrical and control engineering (ICECE), 2010, pp. 2351-2354Google Scholar
  70. 70.
    Wei, L., Najdovski, Z., Abdelrahman, W., Nahavandi, S., Weisinger, H.: Augmented optometry training simulator with multi-point haptics. In: IEEE international conference on systems, man, and cybernetics (SMC), 2012, pp. 2991-2997Google Scholar
  71. 71.
    Gamecho, B., Silva, H., Guerreiro, J., Gardeazabal, L., Abascal, J., A context-aware application to increase elderly users compliance with physical rehabilitation exercises at home via animatronic biofeedback. J. Med. Syst. 39(11):1–11 , 2015.CrossRefGoogle Scholar
  72. 72.
    Rajanna, V., Vo, P., Barth, J., Mjelde, M., Grey, T., Oduola, C., Hammond, T., Kinohaptics: An automated, wearable, haptic assisted, physio-therapeutic system for post-surgery rehabilitation and self-care. J. Med. Syst. 40(3):1–12, 2015.Google Scholar
  73. 73.
    Heng, P.-A., Cheng, C.-Y., Wong, T.-T., Xu, Y., Chui, Y.-P., Chan, K.-M., Tso, S.-K., A virtual-reality training system for knee arthroscopic surgery. IEEE Trans. Inf. Technol. Biomed. 8(2):217–227, 2004.CrossRefPubMedGoogle Scholar
  74. 74.
    Hirche, S., and Buss, M., Human-oriented control for haptic teleoperation. Proc. IEEE 100(3):623–647, 2012.CrossRefGoogle Scholar
  75. 75.
    NVIDIA, PhysX FAQ - NVIDIA, [accessed April-15-2015]. http://www.nvidia.com/object/physxfaq.html
  76. 76.
    Havok, About Havok, [accessed April-15-2015]. http://www.havok.com/about-havok/
  77. 77.
    Newton dynamics, Newton Dynamics - About Newton, [accessed April-15-2015]. http://newtondynamics.com/forum/newton.php
  78. 78.
    Reinkensmeyer, D.J., How to retrain movement after neuro- logic injury: a computational rationale for incorporating robot (or therapist) assistance. IEEE Engineering in Medicine and Biology Society Meeting 2:1479–1482, 2003.Google Scholar
  79. 79.
    Crespo, L.M., Reinkensmeyer, D.J., Effect of robotic guidance on motor learning of a timing task (2008)Google Scholar
  80. 80.
    Powell, D., and O’Malley, M.K.: Efficacy of shared-control guidance paradigms for robot-mediated training.. In: IEEE world haptics conference, pp. 427–432 (2011)Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • David Escobar-Castillejos
    • 1
  • Julieta Noguez
    • 1
  • Luis Neri
    • 2
  • Alejandra Magana
    • 3
  • Bedrich Benes
    • 4
  1. 1.Escuela de Ingenieria y CienciasInstituto Tecnologico y de Estudios Superiores de Monterrey Campus Ciudad de MexicoDistrito FederalMexico
  2. 2.Escuela de Educacion, Humanidades y Ciencias SocialesInstituto Tecnologico y de Estudios Superiores de Monterrey Campus Ciudad de MexicoDistrito FederalMexico
  3. 3.Associate Professor of Computer and Information TechnologyPurdue UniversityIndianaUSA
  4. 4.Professor of Computer Graphics TechnologyPurdue UniversityIndianaUSA

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