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Issue No.04 - Fourth Quarter (2012 vol.5)
pp: 312-322
Tim Horeman , Leiden University Medical Center, Leiden and Delft University of Technology, Delft
Sharon P. Rodrigues , Leiden University Medical Center, Leiden
Frank Willem Jansen , Leiden University Medical Center, Leiden and Delft University of Technology, Delft
Jenny Dankelman , Delft University of Technology, Delft
John J. van den Dobbelsteen , Delft University of Technology, Delft
ABSTRACT
When equipped with motion and force sensors, box-trainers can be good alternatives for relatively expensive Virtual Reality (VR) trainers. As in VR trainers, the sensors in a box trainer could provide the trainee with objective information about his performance. Recently, multiple tracking systems were developed for classification of participants based on motion and time parameters. The aim of this study is the development of force parameters that reflect the trainee's performance in a suture task. Our second goal is to investigate if the level of the participant's skills can be classified as experts or novice level. In the experiment, experts ({\rm n} = 11) and novices ({\rm n} = 21) performed a two-handed needle driving and knot tying task on artificial tissue inside a box trainer. The tissue was mounted on the Force platform that was used to measure the force, which the subject applied on the tissue in three directions. We evaluated the potential of 16 different performance parameters, related to the magnitude, direction, and variability of applied forces, to distinguish between different levels of surgical expertise. Nine of the parameters showed significant differences between experts and novices. Principal Component Analysis was used to convert these nine partly correlating parameters, such as peak force, mean force, and main direction of force, into two uncorrelated variables. By performing a Leave-One-Out-Cross Validation with Linear Discriminant Analysis on each participants' score on these two variables, it was possible to correctly classify 84 percent of all participants as an expert or novice. We conclude that force measurements in a box trainer can be used to classify the level of performance of trainees and can contribute to objective assessment of suture skills.
INDEX TERMS
Force feedback, Needles, Ellipsoids, Laparoscopes, Virtual reality, Principal component analysis, Surgery, Training, objective assessment, Minimally invasive surgery, laparoscopy, box trainers, force feedback, training methods
CITATION
Tim Horeman, Sharon P. Rodrigues, Frank Willem Jansen, Jenny Dankelman, John J. van den Dobbelsteen, "Force Parameters for Skills Assessment in Laparoscopy", IEEE Transactions on Haptics, vol.5, no. 4, pp. 312-322, Fourth Quarter 2012, doi:10.1109/TOH.2011.60
REFERENCES
[1] S.M.B.I. Botden and J.J. Jakimowicz, "What Is Going on in Augmented Reality Simulation in Laparoscopic Surgery? Surgical Endoscopy," vol. 23, no. 8, pp. 1693-1700, 2009.
[2] G. Tholey, J.P. Desai, and A.E. Castellanos, "Force Feedback Plays a Significant Role in Minimally. Annals of Surgery," vol. 241, no. 1, pp. 102-109, 2005.
[3] M. Kitagawa, A.M. Okamura, B.T. Bethea, V.L. Gott, and W.A. Baumgartner, "Analysis of Suture Manipulation Forces for Teleoperation with Force Feedback," Medical Image Computing and Computer-Assisted Intervention vol. 2488, pp. 155-162, 2002.
[4] J.J. Dobbelsteen, A. Schooleman, and, J. Dankelman, "Friction Dynamics of Trocars," Surgical Endoscopy, vol. 21, no. 8, pp. 1338-1343, 2007.
[5] E.P. Westebring-van der Putten, J.J. van den Dobbelsteen, R.H.M. Goossen, J.J. Jakimowicz, and, J. Dankelman, "Effect of Laparoscopic Grasper Force Transmission Ratio on Grasp Control," Surgical Endoscopy, vol. 23, no. 4, pp. 818-824, 2009.
[6] W. Sjoerdsma, J.L. Herder, M.J. Horward, A. Jansen, J.J.G. Bannenberg, and C.A. Grimbergen, "Force Transmission of Laparoscopic Grasping Instruments," Minimally Invasive Therapy and Allied Technologies (MITAT), vol. 6, no. 4, pp. 274-278, 1997.
[7] C.E. Reiley, T. Akinbiyi, D. Burschka, D.C. Chang, A.M. Okamura, and D.D. Yuh, "Effects of Visual Force Feedback on Robot-Assisted Surgical Task Performance," J. Thoracic and Cardiovascular Surgery, vol. 135, no. 1, pp. 196-202, 2008.
[8] M.K. Chmarra, S. Klein, J.C.F. de Winter, F.W. Jansen, and J. Dankelman, "Objective Classification of Residents Based on Their Psychomotor Laparoscopic Skills," Surgical Endoscopy, vol. 24, no. 5, pp. 1031-1039, 2010.
[9] C. Richards, J. Rosen, B. Hannaford, C. Pellegrini, and M.N. Sinanan, "Skills Evaluation in Minimally Invasive Surgery Using Force/torque Signatures," Surgical Endoscopy, vol. 14, no. 9, pp. 791-798, 2000.
[10] J. Rosen, L. Chang, J.D. Brown, B. Hannaford, M. Sinanan, and R. Satava, "Minimally Invasive Surgery Task Decomposition-Etymology of Endoscopic Suturing," Proc. Int'l Conf. Medicine Meets Virtual Reality (MMVR), 2003.
[11] S. Gunther, J. Rosen, B. Hannaford, and M. Sinanan, "The Red DRAGON: A Multi-Modality System for Simulation and Training in Minimally Invasive Surgery," Studies in Health Technology and Informatics, vol. 125, pp. 149-154, 2007.
[12] M.K. Chmarra, N.H. Bakker, C.A. Grimbergen, and J. Dankelman, "TrEndo, A Device for Tracking Minimally Invasive Surgical Instruments in Training Setups," Sensors and Actuators, vol. 126, no. 2, pp. 328-334, 2005.
[13] T. Horeman, S.P. Rodrigues, F.W. Jansen, J. Dankelman, and J.J. Dobbelsteen, "Force Measurement Platform for Training and Assessment of Laparoscopic Skills," Surgical Endoscopy, vol. 24, no. 5, pp. 3102-3108, 2009.
[14] K. Pearson, "On Lines and Planes of Closest Fit to Systems of Points in Space Philosophical Magazine," vol. 2, no. 6, pp. 559-572, 1901.
[15] D.F. Morrison, Multivariate Statistical Methods Singapore, p. 336. McGraw-Hill, 1990.
[16] T.W. Anderson, "The Annals of Mathematical Statistics Institute of Mathematical Statistics," vol. 34, no. 1, pp. 122-148, 1963.
[17] W. Kolkman, M.A.J. Put, R. Wolterbeek, J.B.M.Z. Trimbos, and F.W. Jansen, "Laparoscopic Skills Simulator: Construct Validity and Establishment of Performance Standards for Residency Training," Gynecological Surgery, vol. 5, no. 2, pp. 109-114, 2007.
[18] J. Solis, "Integration of an Evaluation Function into the Suture/Ligature Training System WKS-2R," Proc. IEEE Int'l Conf. Robotics and Automation, pp. 1094-1099, 2008.
[19] R.V. O'Toole, R.R. Playter, and T.M. Krummel, "Measuring and Developing Suturing Technique with a Virtual Reality Surgical Simulator," J. Am. College of Surgeons, vol. 189, no. 1, pp. 114-27, 1999.
[20] P. Breedveld, H.G. Stassen, D.G. Meijer, and L.P.S. Stassen, "Theoretical Background and Conceptual Solution for Depth Perception and Eye-Hand Coordination Problems in Laparoscopic Surgery," Minimally Invasive Therapy & Allied Technologies, vol. 8, no. 4, pp. 227-234, 1999.
[21] M.K. Chmarra, W. Kolkman, F.W. Jansen, C.A. Grimbergen, and J. Dankelman, "The Influence of Experience and Camera Holding on Laparoscopic Instrument Movements Measured with the TrEndo Tracking System," Surgical Endoscopy, vol. 21, no. 11, pp. 1432-2218, 2007.
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