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Publisher: Elsevier BV
Journal: Journal of Surgical Education
Languages: English
Types: Article
Subjects: Education, Surgery
Background: Laparoscopic surgery requires operators to learn novel complex movement patterns. However, our understanding of how best to train surgeons’ motor skills is inadequate and research is needed to determine optimal laparoscopic training regimes. This difficulty is confounded by variables inherent in surgical practice – e.g. the increasing prevalence of morbidly obese patients presents additional challenges related to restriction of movement due to abdominal wall resistance and reduced intra-abdominal space. The aim of this study was to assess learning of a surgery related task in constrained and unconstrained conditions using a novel system linking a commercially available robotic arm with specialised software creating the novel kinematic assessment tool (Omni-KAT). Methods: We created an experimental tool that records motor performance by linking a commercially available robotic arm with specialised software that presents visual stimuli and objectively measures movement outcome (kinematics). Participants were given the task of generating aiming movements along a horizontal plane to move a visual cursor on a vertical screen. One group received training that constrained movements to the correct plane whilst the other group was unconstrained and could explore the entire ‘action space’. Results: The tool successfully generated the requisite force fields and precisely recorded the aiming movements. Consistent with predictions from structural learning theory, the unconstrained group produced better performance after training as indexed by movement duration (p < .05). Conclusion: The data showed improved performance for participants who explored the entire action space, highlighting the importance of learning the full dynamics of laparoscopic instruments. These findings, alongside the development of the Omni-KAT, open up exciting prospects for better understanding of the learning processes behind surgical training and investigating ways in which learning can be optimised.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. Stefanidis D, Korndorffer JR, Markley S, Sierra R, Scott DJ. Proficiency maintenance: impact of ongoing simulator training on laparoscopic skill retention. J Am Coll Surg. 2006;202(4):599-603. http://dx.doi.org/ 10.1016/j.jamcollsurg.2005.12.018.
    • 2. Catchpole K, Panesar SS, Russell J, Tang V, Hibbert P, Cleary K. Surgical safety can be improved through better understanding of incidents reported to a national database. Available at: 〈www.nrls.npsa.
    • nhs.uk〉. Accessed 21.03.16.
    • 3. White A, Skelton M, Mushtaq F, et al. Inconsistent reporting of minimally invasive surgery errors. Ann R Coll Surg Engl. 2015;97(8):608-612. http://dx.doi.org/ 10.1308/rcsann.2015.0038.
    • 4. Bashir G. Technology and medicine: the evolution of virtual reality simulation in laparoscopic training. Med Teach. 2010;32(7):558-561. http://dx.doi.org/10.3109/ 01421590903447708.
    • 5. Haque S, Srinivasan S. A meta-analysis of the training effectiveness of virtual reality surgical simulators. IEEE Trans Inf Technol Biomed. 2006;10(1):51-58. http: //dx.doi.org/10.1109/TITB.2005.855529.
    • 6. Seymour NE. VR to OR: a review of the evidence that virtual reality simulation improves operating room performance. World J Surg. 2008;32(2):182-188. http://dx.doi.org/10.1007/s00268-007-9307-9.
    • 7. Orzech N, Palter VN, Reznick RK, Aggarwal R, Grantcharov TP. A comparison of 2 ex vivo training curricula for advanced laparoscopic skills: a randomized controlled trial. Ann Surg. 2012;255(5):833-839. http://dx.doi.org/10.1097/SLA.0b013e31824aca09.
    • 8. Stefanidis D, Scerbo MW, Sechrist C, Mostafavi A, Heniford BT. Do novices display automaticity during simulator training. Am J Surg. 2008;195(2): 210-213. http://dx.doi.org/10.1016/j.amjsurg.2007. 08.055.
    • 9. Stefanidis D, Scerbo MW, Montero PN, Acker CE, Smith WD. Simulator training to automaticity leads to improved skill transfer compared with traditional proficiency-based training: a randomized controlled trial. Ann Surg. 2012;255(1):30-37. http://dx.doi. org/10.1097/SLA.0b013e318220ef31.
    • 10. Aggarwal R, Grantcharov T, Moorthy K, Hance J, Darzi A. A competency-based virtual reality training curriculum for the acquisition of laparoscopic psychomotor skill. Am J Surg. 2006;191(1):128-133. http: //dx.doi.org/10.1016/j.amjsurg.2005.10.014.
    • 11. Gallagher AG, Ritter EM, Champion H, et al. Virtual reality simulation for the operating room: proficiencybased training as a paradigm shift in surgical skills training. Ann Surg. 2005;241(2):364-372. Available at: 〈http://www.ncbi.nlm.nih.gov/pubmed/15650649〉 [Accessed 14.03.16].
    • 12. Gandolfo F, Mussa-Ivaldi FA, Bizzi E. Motor learning by field approximation (arm trajectories/adaptation/ generalization of learning/regularization/intrinsic coordinates). Neurobiology. 1996;93(9):3843-3846.
    • 13. Wolpert DM, Diedrichsen J, Flanagan JR. Principles of sensorimotor learning. Nat Rev Neurosci. 2011;12(12):739-751. http://dx.doi.org/10.1038/ nrn3112.
    • 14. White AD, Giles O, Sutherland RJ, et al. Minimally invasive surgery training using multiple port sites to improve performance. Surg Endosc. 2014;28(4):1188-1193. http://dx.doi.org/10.1007/s00464-013-3307-7.
    • 15. Culmer PR, Levesley MC, Mon-Williams M, Williams JHG. A new tool for assessing human movement: The Kinematic Assessment Tool. J Neurosci Methods. 2009;184(1):184-192. http://dx.doi.org/10. 1016/j.jneumeth.2009.07.025.
    • 16. Maciel A, Liu Y, Ahn W, Singh TP, Dunnican W, De S. Development of the VBLaST: a virtual basic laparoscopic skill trainer. Int J Med Robot. 2008;4(2): 131-138. http://dx.doi.org/10.1002/rcs.185.
    • 17. Arezzo A, Verra M, Ciuti G, et al. Which manmachine interface for a robotically driven endoscopic capsule for endo and laparoscopic applications? Eur Assoc Endosc Surg. Turin, Italy, June 2011.
    • 18. Mullins J, Mawson C, Nahavandi S Haptic Handwriting Aid for Training and Rehabilitation. In: 2005 IEEE International Conference on Systems, Man and Cybernetics. Vol 3. IEEE:2690-2694. http://dx.doi. org/10.1109/ICSMC.2005.1571556.
    • 19. Braun DA, Mehring C, Wolpert DM. Structure learning in action. Behav Brain Res. 2010;206(2): 157-165. http://dx.doi.org/10.1016/j.bbr.2009.08.031.
    • 20. Braun DA, Aertsen A, Wolpert DM, Mehring C. Report motor task variation induces structural learning. Curr Biol. 2009;19:352-357. http://dx.doi.org/ 10.1016/j.cub.2009.01.036.
    • 21. Turnham EJA, Braun DA, Wolpert DM. Facilitation of learning induced by both random and gradual visuomotor task variation. J Neurophysiol. 2012; 107(4):1111-1122. http://dx.doi.org/10.1152/jn. 00635.2011.
    • 22. Jordan JA, Gallagher AG, McGuigan J, McGlade K, McClure N. A comparison between randomly alternating imaging, normal laparoscopic imaging, and virtual reality training in laparoscopic psychomotor skill acquisition. Am J Surg. 2000;180(3):208-211. Available at: 〈http://www.ncbi.nlm.nih.gov/pubmed/ 11084131〉 [Accessed 14.03.16].
    • 23. Westenberg Y, Smits-Engelsman BCM, Duysens J. Development of unimanual versus bimanual task performance in an isometric task. Available at: 〈http:// dx.doi.org/10.1016/j.humov.2004.08.018〉.
    • 24. Koeneke S, Lutz K, Wüstenberg T, Jäncke L. Bimanual versus unimanual coordination: what makes the difference. Neuroimage. 2004;22(3): 1336-1350. http://dx.doi.org/10.1016/j.neuroimage. 2004.03.012.
    • 25. Johnson RL, Culmer PR, Burke MR, Mon-Williams M, Wilkie RM. Exploring structural learning in handwriting. Exp Brain Res. 2010;207(3-4):291-295. http: //dx.doi.org/10.1007/s00221-010-2438-5.
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