Robotic surgery training and performance
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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.
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.
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.
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.
KeywordsBimanual coordination Electromyography Robotic surgery Skill assessment
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.
- 4.Basmajian JV, DeLuca CJ (1985) Muscles alive: their functions revealed by electromyography. 5th ed. Williams & Wilkins, BaltimoreGoogle Scholar
- 11.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)Google Scholar
- 20.Intuitive Surgical Company Profile (n.d.) Retrieved November 4, 2005 from http://www.intuitivesurgical.com/corporate/companyprofile
- 21.Kelso JAS (1995) Dynamic patterns. MIT Press, Boston, MAGoogle Scholar
- 22.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: 879–897PubMedCrossRefGoogle Scholar
- 23.Kugler PN, Turvey MT (1987) Information, natural law, and the self-assembly of rhythmic movement. Erlbaum, Hillsdale, NJGoogle Scholar
- 25.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 93–119Google Scholar
- 34.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 NetherlandsGoogle Scholar