Abstract
Background
To understand the process of skill acquisition in robotic surgery and to allow useful real-time feedback to surgeons and trainees in future generations of robotic surgical systems, robotic surgical skills should be determined with objective variables. The aim of this study was to assess skill acquisition through a training protocol, and to identify variables for the quantification of proficiency.
Methods
Seven novice users of the da Vinci Surgical System engaged in 4 weeks of training that involved practicing three bimanual tasks with the system. Seven variables were determined for assessing speed of performance, bimanual coordination, and muscular activation. These values were compared before and after training.
Results
Significant improvements were observed through training in five variables. Bimanual coordination showed differences between the surgical tasks used, whereas muscular activation patterns showed better muscle use through training. The subjects also performed the surgical tasks considerably faster within the first two to three training sessions.
Conclusions
The study objectively demonstrated that the novice users could learn to perform surgical tasks faster and with more consistency, better bimanual dexterity, and better muscular activity utilization. The variables examined showed great promise as objective indicators of proficiency and skill acquisition in robotic surgery.
Similar content being viewed by others
References
Ballantyne GH (2002) Robotic surgery, telerobotic surgery, telepresence, and telemonitoring. Surg Endosc 16: 1389–1402
Ballantyne GH, Moll F (2003) The da Vinci telerobotic surgical system: the virtual operative field and telepresence surgery. Surg Clin North Am 83: 1293–1304
Bann SD, Khan MS, Darzi A (2003) Measurement of surgical dexterity using motion analysis of simple bench tasks. World J Surg 27: 390–394
Basmajian JV, DeLuca CJ (1985) Muscles alive: their functions revealed by electromyography. 5th ed. Williams & Wilkins, Baltimore
Berguer R, Rab GT, Abu-Ghaida H, Alarcon A, Chung J (1997) A comparison of surgeons’ posture during laparoscopic and open surgical procedures. Surg Endosc 11: 139–142
Chapman WH III, Albrecht RJ, Kim VB, Young JA, Chitwood WR Jr (2002) Computer-assisted laparoscopic splenectomy with the da Vinci surgical robot. J Laparoendosc Adv Surg Tech A 12: 155–159
Corcione F, Esposito C, Cuccurullo D, Settembre A, Miranda N, Amato F, Pirozzi F, Caiazzo P (2005) Advantage and limits of robot-assisted laparoscopic surgery: preliminary experience. Surg Endosc 19: 117–119
Dakin GF, Gagner M (2003) Comparison of laparoscopic skills performance between standard instruments and two surgical robotic systems. Surg Endosc 17: 574–579
D’Annibale A, Fiscon V, Trevisan P, Pozzobon M, Gianfreda V, Sovernigo G, Morpurgo E, Orsini C, DelMonte D (2004) The da Vinci robot in right adrenalectomy: considerations on technique. Surg Laparosc Endosc Percutan Tech 14: 38–41
DeUgarte DA, Etzioni DA, Gracia C, Atkinson JB (2003) Robotic surgery an resident training. Surg Endosc 17: 960–963
DiMartino A, Verner L, Narazaki K, Hallbeck MS, Oleynikov D (2005) Effect of visual feedback on surgical performance using da VinciTM surgical system. J Laparoendosc Adv Surg Tech A (in review)
Gallagher AG, Richie K, McClure N, McGuigan J (2001) Objective psychomotor skills assessment of experienced, junior, and novice laparoscopists with virtual reality. World J Surg 25: 1478–1483
Garcia-Ruiz A, Gagner M, Miller J, Steiner CP, Hahn JF (1998) Manual vs robotically assisted laparoscopic surgery in the performance of basic manipulation and suturing tasks. Arch Surg 133: 957–961
Gutt CN, Oniu T, Mehrabi A, Kashfi A, Schemmer P, Buchler MW (2004) Roboti-assisted abdominal surgery. Br J Surg 91: 1390–1397
Gutt CN, Oniu T, Schemmer P, Mehrabi A, Buchler MW (2004) Fewer adhesions induced by laparoscopic surgery? Surg Endosc 18: 898–906
Haken H, Kelso JAS, Bunz H (1985) A theoretical model of phase transitions in human hand movements. Biol Cybern 51: 347–356
Hanly EJ, Talamini MA (2004) Robotic abdominal surgery. Am J Surg 188(4A): 19S–26S
Hernandez JD, Bann SD, Munz Y, Moorthy K, Datta V, Martin S, Dosis A, Bello F, Darzi A, Rockall T (2004) Qualitative and quantitative analysis of the learning curve of a simulated surgical task on the da Vinci system. Surg Endosc 18: 372–378
Horgan S, Vanuno D (2001) Robots in laparoscopic surgery. J Laparoendosc Adv Surg Tech A 11: 415–419
Intuitive Surgical Company Profile (n.d.) Retrieved November 4, 2005 from http://www.intuitivesurgical.com/corporate/companyprofile
Kelso JAS (1995) Dynamic patterns. MIT Press, Boston, MA
Korolija D, Sauerland S, Wood-Dauphinee S, Abbou CC, Eypasch E, Garcia Caballero M, Lumsden MA, Millat B, Monson JRT, Nilsson G, Pointner R, Schwenk W, Shamiyeh A, Szold A, Targarona E, Ure B, Neugebauer E (2004) Evaluation of quality of life after laparoscopic surgery. Surg Endosc 18: 879–897
Kugler PN, Turvey MT (1987) Information, natural law, and the self-assembly of rhythmic movement. Erlbaum, Hillsdale, NJ
Kurz MJ, Stergiou N (2002) Effect of normalization and phase angle calculations on continuous relative phase. J Biomech 35: 369–374
Kurz MJ, Stergiou N (2004) Applied dynamic systems theory for the analysis of movement. In: Stergiou N (ed) Innovative analyses of human movement. Human Kinetics Publishers, Champaign, IL pp 93–119
Moorthy K, Munz Y, Dosis A, Hernandez J, Martin S, Bello F, Rockall T, Darzi A (2004) Dexterity enhancement with robotic surgery. Surg Endosc 18: 790–795
Prasad SM, Maniar HS, Soper NJ, Damiano RJ, Klingensmith ME (2002) The effect of robotic assistance on learning curves for basic laparoscopic skills. Am J Surg 183: 702–707
Quick NE, Gillete JC, Shapiro R, Adrales GL, Gerlach D, Park AE (2003) The effect of using laparoscopic instruments on muscle activation patterns during minimally invasive surgery. Surg Endosc 17: 462–465
Ruurda JP, Broeders IA, Simmermacher RP, Rinkes IH, VanVroonhoven TJ (2002) Feasibility of robot-assisted laparoscopic surgery: an evaluation of 35 robot-assisted laparoscopic cholecystectomies. Surg Laparosc Endosc Percutan Tech 12: 41–45
Sarle R, Tewari A, Shrivastava A, Peabody J, Menon M (2004) Surgical robotics and laparoscopic training drills. J Endourol 18: 63–67
Smith CD, Farrell TM, McNatt SS, Metreveli RE (2001) Assessing laparoscopic manipulative skills. Am J Surg 181: 547–550
Talamini MA, Stanfield CL, Chang DC, Wu AW (2004) The surgical recovery index. Surg Endosc 18: 596–600
Turvey MT (1990) Coordination. Am Psychol 45: 938–953
Verner L, Oleynikov D, Holtmann S, Haider H, Zhukov L (2003) Measurements of the level of surgical expertise using flight path analysis from da VinciTM robotic surgical system. In: Westwood JD (ed). Medicine meets virtual reality. IOS Press, Amsterdam, The Netherlands
Yohannes P, Rotariu P, Pinto P, Smith AD, Lee BR (2002) Comparison of robotic versus laparoscopic skills: is there a difference in the learning curve? Urology 60: 39–45
Acknowledgments
The authors thank Jesse Pandorf for his assistance with subject recruitment and data collection. They also thank Ben Solomon for his assistance with the data analysis. This study was supported in part by a grant from the Nebraska Research Initiative awarded to Drs. Oleynikov and Stergiou.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Narazaki, K., Oleynikov, D. & Stergiou, N. Robotic surgery training and performance. Surg Endosc 20, 96–103 (2006). https://doi.org/10.1007/s00464-005-3011-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00464-005-3011-3