Skip to main content
Top
Published in: Surgical Endoscopy 7/2014

01-07-2014

Effects of robotic manipulators on movements of novices and surgeons

Authors: Ilana Nisky, Allison M. Okamura, Michael H. Hsieh

Published in: Surgical Endoscopy | Issue 7/2014

Login to get access

Abstract

Background

Robot-assisted surgery is widely adopted for many procedures but has not realized its full potential to date. Based on human motor control theories, the authors hypothesized that the dynamics of the master manipulators impose challenges on the motor system of the user and may impair performance and slow down learning. Although studies have shown that robotic outcomes are correlated with the case experience of the surgeon, the relative contribution of cognitive versus motor skill is unknown. This study quantified the effects of da Vinci Si master manipulator dynamics on movements of novice users and experienced surgeons and suggests possible implications for training and robot design.

Methods

In the reported study, six experienced robotic surgeons and ten novice nonmedical users performed movements under two conditions: teleoperation of a da Vinci Si Surgical system and freehand. A linear mixed model was applied to nine kinematic metrics (including endpoint error, movement time, peak speed, initial jerk, and deviation from a straight line) to assess the effects of teleoperation and expertise. To assess learning effects, t tests between the first and last movements of each type were used.

Results

All the users moved slower during teleoperation than during freehand movements (F 1,9343 = 345; p < 0.001). The experienced surgeons had smaller errors than the novices (F 1,14 = 36.8; p < 0.001). The straightness of movements depended on their direction (F 7,9343 = 117; p < 0.001). Learning effects were observed in all conditions. Novice users first learned the task and then the dynamics of the manipulator.

Conclusions

The findings showed differences between the novices and the experienced surgeons for extremely simple point-to-point movements. The study demonstrated that manipulator dynamics affect user movements, suggesting that these dynamics could be improved in future robot designs. The authors showed the partial adaptation of novice users to the dynamics. Future studies are needed to evaluate whether it will be beneficial to include early training sessions dedicated to learning the dynamics of the manipulator.
Literature
1.
go back to reference Maeso S, Reza M, Mayol JA et al (2010) Efficacy of the Da Vinci Surgical System in abdominal surgery compared with that of laparoscopy: a systematic review and meta-analysis. Ann Surg 252:254–262PubMedCrossRef Maeso S, Reza M, Mayol JA et al (2010) Efficacy of the Da Vinci Surgical System in abdominal surgery compared with that of laparoscopy: a systematic review and meta-analysis. Ann Surg 252:254–262PubMedCrossRef
4.
go back to reference Moorthy K, Munz Y, Dosis A et al (2004) Dexterity enhancement with robotic surgery. Surg Endosc 18:790–795PubMedCrossRef Moorthy K, Munz Y, Dosis A et al (2004) Dexterity enhancement with robotic surgery. Surg Endosc 18:790–795PubMedCrossRef
5.
go back to reference Rassweiler J, Hruza M, Teber D et al (2006) Laparoscopic and robotic-assisted radical prostatectomy: critical analysis of the results. Eur Urol 49:612–624PubMedCrossRef Rassweiler J, Hruza M, Teber D et al (2006) Laparoscopic and robotic-assisted radical prostatectomy: critical analysis of the results. Eur Urol 49:612–624PubMedCrossRef
6.
go back to reference Marescaux J, Leroy J, Rubino F et al (2002) Transcontinental robot-assisted remote telesurgery: feasibility and potential applications. Ann Surg 235:487–492PubMedCentralPubMedCrossRef Marescaux J, Leroy J, Rubino F et al (2002) Transcontinental robot-assisted remote telesurgery: feasibility and potential applications. Ann Surg 235:487–492PubMedCentralPubMedCrossRef
7.
8.
go back to reference Reznick RK, MacRae H (2006) Teaching surgical skills: changes in the wind. N Engl J Med 355:2664–2669PubMedCrossRef Reznick RK, MacRae H (2006) Teaching surgical skills: changes in the wind. N Engl J Med 355:2664–2669PubMedCrossRef
9.
go back to reference Schout BMA, Hendrikx AJM, Scheele F et al (2010) Validation and implementation of surgical simulators: a critical review of present, past, and future. Surg Endosc 24:536–546PubMedCentralPubMedCrossRef Schout BMA, Hendrikx AJM, Scheele F et al (2010) Validation and implementation of surgical simulators: a critical review of present, past, and future. Surg Endosc 24:536–546PubMedCentralPubMedCrossRef
11.
go back to reference Ericsson KA (2004) Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Acad Med 79:S70–S81PubMedCrossRef Ericsson KA (2004) Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Acad Med 79:S70–S81PubMedCrossRef
12.
go back to reference Ugarte DA, Etzioni DA, Gracia C et al (2003) Robotic surgery and resident training. Surg Endosc 17:960–963PubMedCrossRef Ugarte DA, Etzioni DA, Gracia C et al (2003) Robotic surgery and resident training. Surg Endosc 17:960–963PubMedCrossRef
13.
go back to reference Narazaki K, Oleynikov D, Stergiou N (2006) Robotic surgery training and performance. Surg Endosc 20:96–103PubMedCrossRef Narazaki K, Oleynikov D, Stergiou N (2006) Robotic surgery training and performance. Surg Endosc 20:96–103PubMedCrossRef
14.
go back to reference Tausch TJ, Kowalewski TM, White LW et al (2012) Content and construct validation of a robotic surgery curriculum using an electromagnetic instrument tracker. J Urol 188:919–923PubMedCrossRef Tausch TJ, Kowalewski TM, White LW et al (2012) Content and construct validation of a robotic surgery curriculum using an electromagnetic instrument tracker. J Urol 188:919–923PubMedCrossRef
15.
go back to reference Reiley CE, Lin HC, Yuh DD et al (2011) Review of methods for objective surgical skill evaluation. Surg Endosc 25:356–366PubMedCrossRef Reiley CE, Lin HC, Yuh DD et al (2011) Review of methods for objective surgical skill evaluation. Surg Endosc 25:356–366PubMedCrossRef
16.
go back to reference Shadmehr R, Mussa-Ivaldi S (2012) Biological learning and control: how the brain builds representations, predicts events, and makes decisions. MIT Press, CambridgeCrossRef Shadmehr R, Mussa-Ivaldi S (2012) Biological learning and control: how the brain builds representations, predicts events, and makes decisions. MIT Press, CambridgeCrossRef
17.
go back to reference Lin H, Shafran I, Yuh D et al (2006) Towards automatic skill evaluation: detection and segmentation of robot-assisted surgical motions. Comput Aided Surg 11:220–230PubMedCrossRef Lin H, Shafran I, Yuh D et al (2006) Towards automatic skill evaluation: detection and segmentation of robot-assisted surgical motions. Comput Aided Surg 11:220–230PubMedCrossRef
18.
go back to reference Rosen J, Brown JD, Chang L et al (2006) Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model. IEEE Trans Biomed Eng 53:399–413PubMedCrossRef Rosen J, Brown JD, Chang L et al (2006) Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model. IEEE Trans Biomed Eng 53:399–413PubMedCrossRef
19.
go back to reference Megali G, Sinigaglia S, Tonet O et al (2006) Modelling and evaluation of surgical performance using hidden Markov models. IEEE Trans Biomed Eng 53:1911–1919PubMedCrossRef Megali G, Sinigaglia S, Tonet O et al (2006) Modelling and evaluation of surgical performance using hidden Markov models. IEEE Trans Biomed Eng 53:1911–1919PubMedCrossRef
20.
go back to reference Lendvay TS, Brand TC, White L et al (2013) Virtual reality robotic surgery warmup improves task performance in a dry laboratory environment: a prospective randomized controlled study. J Am Coll Surg 216:1181–1192PubMedCrossRef Lendvay TS, Brand TC, White L et al (2013) Virtual reality robotic surgery warmup improves task performance in a dry laboratory environment: a prospective randomized controlled study. J Am Coll Surg 216:1181–1192PubMedCrossRef
21.
go back to reference Judkins T, Oleynikov D, Stergiou N (2009) Objective evaluation of expert and novice performance during robotic surgical training tasks. Surg Endosc 23:590–597PubMedCrossRef Judkins T, Oleynikov D, Stergiou N (2009) Objective evaluation of expert and novice performance during robotic surgical training tasks. Surg Endosc 23:590–597PubMedCrossRef
22.
go back to reference Chmarra M, Klein S, Winter JF et al (2010) Objective classification of residents based on their psychomotor laparoscopic skills. Surg Endosc 24:1031–1039PubMedCentralPubMedCrossRef Chmarra M, Klein S, Winter JF et al (2010) Objective classification of residents based on their psychomotor laparoscopic skills. Surg Endosc 24:1031–1039PubMedCentralPubMedCrossRef
23.
go back to reference Hofstad EF, Våpenstad C, Chmarra MK et al (2013) A study of psychomotor skills in minimally invasive surgery: what differentiates expert and nonexpert performance. Surg Endosc 27:854–863PubMedCrossRef Hofstad EF, Våpenstad C, Chmarra MK et al (2013) A study of psychomotor skills in minimally invasive surgery: what differentiates expert and nonexpert performance. Surg Endosc 27:854–863PubMedCrossRef
24.
go back to reference Peters J, Fried GM, Swanstrom LL et al (2004) Development and validation of a comprehensive program of education and assessment of the basic fundamentals of laparoscopic surgery. Surgery 135:21–27PubMedCrossRef Peters J, Fried GM, Swanstrom LL et al (2004) Development and validation of a comprehensive program of education and assessment of the basic fundamentals of laparoscopic surgery. Surgery 135:21–27PubMedCrossRef
25.
go back to reference Flash T, Hogan N (1985) The coordination of arm movements: an experimentally confirmed mathematical model. J Neurosci 5:1688–1703PubMed Flash T, Hogan N (1985) The coordination of arm movements: an experimentally confirmed mathematical model. J Neurosci 5:1688–1703PubMed
26.
go back to reference Scheidt RA, Ghez C (2007) Separate adaptive mechanisms for controlling trajectory and final position in reaching. J Neurophysiol 98:3600–3613PubMedCrossRef Scheidt RA, Ghez C (2007) Separate adaptive mechanisms for controlling trajectory and final position in reaching. J Neurophysiol 98:3600–3613PubMedCrossRef
27.
go back to reference Fitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381–391PubMedCrossRef Fitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381–391PubMedCrossRef
30.
go back to reference Gaba DM, Howard SK (2002) Fatigue among clinicians and the safety of patients. N Engl J Med 347:1249–1255PubMedCrossRef Gaba DM, Howard SK (2002) Fatigue among clinicians and the safety of patients. N Engl J Med 347:1249–1255PubMedCrossRef
31.
go back to reference Holzman IR, Barnett SH (2000) The Bell Commission: ethical implications for the training of physicians. Mount Sinai J Med 67:136–139 Holzman IR, Barnett SH (2000) The Bell Commission: ethical implications for the training of physicians. Mount Sinai J Med 67:136–139
32.
go back to reference Shmuelof L, Krakauer JW, Mazzoni P (2012) How is a motor skill learned? Change and invariance at the levels of task success and trajectory control. J Neurophysiol 108:578–594PubMedCentralPubMedCrossRef Shmuelof L, Krakauer JW, Mazzoni P (2012) How is a motor skill learned? Change and invariance at the levels of task success and trajectory control. J Neurophysiol 108:578–594PubMedCentralPubMedCrossRef
33.
go back to reference Colonnese N, Okamura AM (2012) M-width: stability and accuracy of haptic rendering of virtual mass. In: Robotics: science and systems Colonnese N, Okamura AM (2012) M-width: stability and accuracy of haptic rendering of virtual mass. In: Robotics: science and systems
34.
go back to reference Wolpert DM, Kawato M (1998) Multiple paired forward and inverse models for motor control. Neural Networks 11:1317–1329PubMedCrossRef Wolpert DM, Kawato M (1998) Multiple paired forward and inverse models for motor control. Neural Networks 11:1317–1329PubMedCrossRef
35.
go back to reference Krakauer JW, Pine ZM, Ghilardi M-F et al (2000) Learning of visuomotor transformations for vectorial planning of reaching trajectories. J Neurosci 20:8916–8924PubMed Krakauer JW, Pine ZM, Ghilardi M-F et al (2000) Learning of visuomotor transformations for vectorial planning of reaching trajectories. J Neurosci 20:8916–8924PubMed
36.
go back to reference Kluzik J, Diedrichsen J, Shadmehr R et al (2008) Reach adaptation: what determines whether we learn an internal model of the tool or adapt the model of our arm? J Neurophysiol 100:1455–1464PubMedCentralPubMedCrossRef Kluzik J, Diedrichsen J, Shadmehr R et al (2008) Reach adaptation: what determines whether we learn an internal model of the tool or adapt the model of our arm? J Neurophysiol 100:1455–1464PubMedCentralPubMedCrossRef
37.
go back to reference Lackner JR, Dizio P (1994) Rapid adaptation to Coriolis force perturbations of arm trajectory. J Neurophysiol 72:299–313PubMed Lackner JR, Dizio P (1994) Rapid adaptation to Coriolis force perturbations of arm trajectory. J Neurophysiol 72:299–313PubMed
39.
go back to reference Shadmehr R, Mussa-Ivaldi FA (1994) Adaptive representation of dynamics during learning of a motor task. J Neurosci 14:3208–3224PubMed Shadmehr R, Mussa-Ivaldi FA (1994) Adaptive representation of dynamics during learning of a motor task. J Neurosci 14:3208–3224PubMed
40.
go back to reference Imamizu H, Miyauchi S, Tamada T et al (2000) Human cerebellar activity reflecting an acquired internal model of a new tool. Nature 403:192–195PubMedCrossRef Imamizu H, Miyauchi S, Tamada T et al (2000) Human cerebellar activity reflecting an acquired internal model of a new tool. Nature 403:192–195PubMedCrossRef
41.
go back to reference Maravita A, Iriki A (2004) Tools for the body (schema). Trends Cognitive Sci 8:79–86CrossRef Maravita A, Iriki A (2004) Tools for the body (schema). Trends Cognitive Sci 8:79–86CrossRef
42.
go back to reference Cardinali L, Frassinetti F, Brozzoli C et al (2009) Tool-use induces morphological updating of the body schema. Curr Biol 19:1157CrossRef Cardinali L, Frassinetti F, Brozzoli C et al (2009) Tool-use induces morphological updating of the body schema. Curr Biol 19:1157CrossRef
43.
go back to reference Leib R, Karniel A (2012) Minimum acceleration with constraints of center of mass: a unified model for arm movements and object manipulation. J Neurophysiol 108:1646–1655PubMedCrossRef Leib R, Karniel A (2012) Minimum acceleration with constraints of center of mass: a unified model for arm movements and object manipulation. J Neurophysiol 108:1646–1655PubMedCrossRef
44.
go back to reference Seymour NE, Gallagher AG, Roman SA et al (2002) Virtual reality training improves operating room performance: results of a randomized, double-blinded study. Ann Surg 236:458–464PubMedCentralPubMedCrossRef Seymour NE, Gallagher AG, Roman SA et al (2002) Virtual reality training improves operating room performance: results of a randomized, double-blinded study. Ann Surg 236:458–464PubMedCentralPubMedCrossRef
45.
go back to reference Matsumoto ED, Hamstra SJ, Radomski SB et al (2002) The effect of bench model fidelity on endourological skills: a randomized controlled study. J Urol 167:1243–1247PubMedCrossRef Matsumoto ED, Hamstra SJ, Radomski SB et al (2002) The effect of bench model fidelity on endourological skills: a randomized controlled study. J Urol 167:1243–1247PubMedCrossRef
46.
go back to reference Anastakis DJ, Regehr G, Reznick RK et al (1999) Assessment of technical skills transfer from the bench training model to the human model. Am J Surg 177:167–170PubMedCrossRef Anastakis DJ, Regehr G, Reznick RK et al (1999) Assessment of technical skills transfer from the bench training model to the human model. Am J Surg 177:167–170PubMedCrossRef
47.
go back to reference Grober ED, Hamstra SJ, Wanzel KR et al (2004) The educational impact of bench model fidelity on the acquisition of technical skill: the use of clinically relevant outcome measures. Ann Surg 240:374–381PubMedCentralPubMedCrossRef Grober ED, Hamstra SJ, Wanzel KR et al (2004) The educational impact of bench model fidelity on the acquisition of technical skill: the use of clinically relevant outcome measures. Ann Surg 240:374–381PubMedCentralPubMedCrossRef
48.
go back to reference Klein J, Spencer SJ, Reinkensmeyer DJ (2012) Breaking it down is better: haptic decomposition of complex movements aids in robot-assisted motor learning: neural systems and rehabilitation engineering. IEEE Trans 20:268–275 Klein J, Spencer SJ, Reinkensmeyer DJ (2012) Breaking it down is better: haptic decomposition of complex movements aids in robot-assisted motor learning: neural systems and rehabilitation engineering. IEEE Trans 20:268–275
49.
go back to reference Penhune VB, Steele CJ (2012) Parallel contributions of cerebellar, striatal, and M1 mechanisms to motor sequence learning. Behav Brain Res 226:579–591PubMedCrossRef Penhune VB, Steele CJ (2012) Parallel contributions of cerebellar, striatal, and M1 mechanisms to motor sequence learning. Behav Brain Res 226:579–591PubMedCrossRef
50.
go back to reference Arora S, Aggarwal R, Sirimanna P et al (2011) Mental practice enhances surgical technical skills: a randomized controlled study. Ann Surg 253:265–270PubMedCrossRef Arora S, Aggarwal R, Sirimanna P et al (2011) Mental practice enhances surgical technical skills: a randomized controlled study. Ann Surg 253:265–270PubMedCrossRef
Metadata
Title
Effects of robotic manipulators on movements of novices and surgeons
Authors
Ilana Nisky
Allison M. Okamura
Michael H. Hsieh
Publication date
01-07-2014
Publisher
Springer US
Published in
Surgical Endoscopy / Issue 7/2014
Print ISSN: 0930-2794
Electronic ISSN: 1432-2218
DOI
https://doi.org/10.1007/s00464-014-3446-5

Other articles of this Issue 7/2014

Surgical Endoscopy 7/2014 Go to the issue