Towards integrating task information in skills assessment for dexterous tasks in surgery and simulation

With the increasing popularity of robotic surgery, several studies in the literature have investigated automatically assessing skill measures based on motion and video data captured from these systems. A range of simulation environments for robotic surgery are now in development. Skill assessment in these environments has so far only focused on evaluating the utility and validity of statistics such as task completion time, and instrument distance measured during a simulated task. We present the first work using motion data from a robotic surgery simulation environment in development for classifying users of varying skills and detecting completion of trainee. Given the standardized environment of the simulator, and the availability of the ground truth, skill measurements and feedback based on task motion hold the promise of effective automated objective assessment. Based on motion data of a simulated manipulation task from 17 users of varying skills, we demonstrate binary classification (proficient vs. trainee) of user skill with 87.5% accuracy. Alternate measures based on instrument pose more relevant in the simulated environment including a new measure of motion efficiency are also presented and evaluated.

[1]  Mani Menon,et al.  Learning curve using robotic surgery , 2006, Current urology reports.

[2]  A. Moinzadeh,et al.  Face, content, and construct validity of dV-trainer, a novel virtual reality simulator for robotic surgery. , 2009, Urology.

[3]  David G. Stork,et al.  Pattern classification, 2nd Edition , 2000 .

[4]  Ross J. Scalese,et al.  Simulation Technology for Skills Training and Competency Assessment in Medical Education , 2007, Journal of General Internal Medicine.

[5]  J. Boggess,et al.  Robotic surgery in gynecologic oncology: evolution of a new surgical paradigm , 2007, Journal of robotic surgery.

[6]  Xiaoying Qi.  Face , 2011, Definitions.

[7]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[8]  R. Satava.  Historical Review of Surgical Simulation—A Personal Perspective , 2008, World Journal of Surgery.

[9]  Parvati Dev,et al.  Comparison of training on two laparoscopic simulators and assessment of skills transfer to surgical performance. , 2005, Journal of the American College of Surgeons.

[10]  Mani Menon,et al.  Evolution of robotic radical prostatectomy , 2007, Cancer.

[11]  Ashutosh Tewari,et al.  Surgical robotics and laparoscopic training drills. , 2004, Journal of endourology.

[12]  Gregory D. Hager,et al.  Towards automatic skill evaluation: detection and segmentation of robot-assisted surgical motions. , 2006 .

[13]  Blake Hannaford,et al.  Markov modeling of minimally invasive surgery based on tool/tissue interaction and force/torque signatures for evaluating surgical skills , 2001, IEEE Transactions on Biomedical Engineering.

[14]  M. Lerner,et al.  Does training on a virtual reality robotic simulator improve performance on the da Vinci surgical system? , 2010, Journal of endourology.

[15]  W Randolph Chitwood,et al.  Current status of endoscopic and robotic mitral valve surgery. , 2005, The Annals of thoracic surgery.

[16]  Evelio Rodriguez,et al.  Outcomes in robotic cardiac surgery , 2007, Journal of robotic surgery.

[17]  Thomas S. Lendvay,et al.  Initial validation of a virtual-reality robotic simulator , 2008, Journal of robotic surgery.

[18]  M. Shuford.  Robotically Assisted Laparoscopic Radical Prostatectomy: A Brief Review of Outcomes , 2007, Proceedings.

[19]  A. Darzi,et al.  Qualitative and quantitative analysis of the learning curve of a simulated surgical task on the da Vinci system , 2004, Surgical Endoscopy And Other Interventional Techniques.

[20]  T. Judkins,et al.  Objective evaluation of expert and novice performance during robotic surgical training tasks , 2009, Surgical Endoscopy.

[21]  T. Grantcharov,et al.  Randomized clinical trial of virtual reality simulation for laparoscopic skills training , 2004, The British journal of surgery.

[22]  R. Satava,et al.  Robotic surgery: identifying the learning curve through objective measurement of skill , 2003, Surgical Endoscopy And Other Interventional Techniques.

[23]  John Kenneth Salisbury,et al.  The Intuitive/sup TM/ telesurgery system: overview and application , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[24]  James R Korndorffer,et al.  Simulator training for laparoscopic suturing using performance goals translates to the operating room. , 2005, Journal of the American College of Surgeons.

[25]  A. Duffy,et al.  Evolution of surgical skills training. , 2006, World journal of gastroenterology.

[26]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.