Performance Optimization of Force Feedback Control System in Virtual Vascular Intervention Surgery

In virtual surgery of minimally invasive vascular intervention, the force feedback is transmitted through the flexible guide wire. The disturbance caused by the flexible deformation would affect the fidelity of the VR (virtual reality) training. SMC (sliding mode control) strategy with delayed-output observer is adopted to suppress the effect of flexible deformation. In this study, the control performance of the strategy is assessed when the length of guide wire between actuator and the operating point changes. The performance assessment results demonstrate the effectiveness of the proposed method and find the optimal length of guide wire for the force feedback control.

[1]  Grigore C. Burdea,et al.  Force and Touch Feedback for Virtual Reality , 1996 .

[2]  Nina F. Thornhill,et al.  Alternative solutions to multi-variate control performance assessment problems q , 2006 .

[3]  Marlies P. Schijven,et al.  European consensus on a competency-based virtual reality training program for basic endoscopic surgical psychomotor skills , 2010, Surgical Endoscopy.

[4]  Daehie Hong,et al.  Haptic-based resistance training machine and its application to biceps exercises , 2011 .

[5]  Christopher R. Wagner,et al.  Force Feedback Benefit Depends on Experience in Multiple Degree of Freedom Robotic Surgery Task , 2007, IEEE Transactions on Robotics.

[6]  Yuan-Shin Lee,et al.  Snapping algorithm and heterogeneous bio-tissues modeling for medical surgical simulation and product prototyping , 2007 .

[7]  弗雷德里克·奥尔森 An interventional simulation device , 2003 .

[8]  Michael Defoort,et al.  Sliding-Mode Formation Control for Cooperative Autonomous Mobile Robots , 2008, IEEE Transactions on Industrial Electronics.

[9]  Anthony G. Gallagher,et al.  Construct validation of a novel hybrid virtual-reality simulator for training and assessing laparoscopic colectomy; results from the first course for experienced senior laparoscopic surgeons , 2008, Surgical Endoscopy.

[10]  Walter Herzog,et al.  Feedback controlled force enhancement and activation reduction of voluntarily activated quadriceps femoris during sub-maximal muscle action. , 2012, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[11]  Yuru Zhang,et al.  Toward In-Vivo Force and Motion Measurement for Vascular Surgery , 2014, IEEE Transactions on Instrumentation and Measurement.

[12]  P. Lamata,et al.  Tissue consistency perception in laparoscopy to define the level of fidelity in virtual reality simulation , 2006, Surgical Endoscopy And Other Interventional Techniques.

[13]  Stephen P. Buerger,et al.  Complementary Stability and Loop Shaping for Improved Human–Robot Interaction , 2007, IEEE Transactions on Robotics.

[14]  Theo Arts,et al.  Computational modeling of volumetric soft tissue growth: application to the cardiac left ventricle , 2009, Biomechanics and modeling in mechanobiology.

[15]  Ning Wang,et al.  Output feedback variable structure control of uncertain linear systems in the presence of actuator dynamics , 2009 .

[16]  P. Lanzer,et al.  Catheter-based cardiovascular interventions , 2013 .

[17]  John Kenneth Salisbury,et al.  Stability of Haptic Rendering: Discretization, Quantization, Time Delay, and Coulomb Effects , 2006, IEEE Transactions on Robotics.

[18]  Bernhard Preim,et al.  Sinus Endoscopy - Application of Advanced GPU Volume Rendering for Virtual Endoscopy , 2008, IEEE Transactions on Visualization and Computer Graphics.

[19]  Mohieddine Jelali,et al.  An overview of control performance assessment technology and industrial applications , 2006 .

[20]  Hans Knutsson,et al.  Simulation of Patient Specific Cervical Hip Fracture Surgery With a Volume Haptic Interface , 2008, IEEE Transactions on Biomedical Engineering.

[21]  Biao Huang,et al.  Multi-step prediction error approach for controller performance monitoring , 2010 .

[22]  Kai-Yuan Cai,et al.  Tracking control for a velocity-sensorless VTOL aircraft with delayed outputs , 2009, Autom..

[23]  Lucian Panait,et al.  The role of haptic feedback in laparoscopic simulation training. , 2009, The Journal of surgical research.

[24]  Tianmiao Wang,et al.  Vascular deformation for vascular interventional surgery simulation , 2010, The international journal of medical robotics + computer assisted surgery : MRCAS.

[25]  Katherine J. Kuchenbecker,et al.  Improving contact realism through event-based haptic feedback , 2006, IEEE Transactions on Visualization and Computer Graphics.

[26]  E. Evgeniou,et al.  Assessment methods in surgical training in the United Kingdom , 2013, Journal of educational evaluation for health professions.

[27]  Farid Ferguene,et al.  Dynamic External Force Feedback Loop Control of a Robot Manipulator Using a Neural Compensator—Application to the Trajectory Following in an Unknown Environment , 2009, Int. J. Appl. Math. Comput. Sci..

[28]  Zhi Zhang,et al.  Performance assessment for a class of nonlinear systems , 2011, 2011 Chinese Control and Decision Conference (CCDC).

[29]  Lucy Y. Pao,et al.  Isotropic force control for haptic interfaces , 2004 .

[30]  Xinkai Chen,et al.  Adaptive sliding mode control for discrete-time multi-input multi-output systems , 2006, Autom..

[31]  Shuxiang Guo,et al.  A novel master-slave robotic catheter system for Vascular Interventional Surgery , 2013, 2013 IEEE International Conference on Mechatronics and Automation.

[32]  Thomas J. Harris,et al.  Controller assessment for a class of non-linear systems , 2007 .

[33]  Alan Myers,et al.  Analysis of discrete time schemes for milling forces control under fractional order holds , 2013 .

[34]  R. Ocampo-Pérez,et al.  Adsorption of Fluoride from Water Solution on Bone Char , 2007 .

[35]  CM Haggerty,et al.  Hemodynamic assessment of virtual surgery options for a failing Fontan using lumped parameter simulation , 2009, 2009 36th Annual Computers in Cardiology Conference (CinC).

[36]  Zhi Zhang,et al.  Performance assessment for the water level control system in steam generator of the nuclear power plant , 2011, Proceedings of the 30th Chinese Control Conference.

[37]  Caroline Jay,et al.  Modeling the effects of delayed haptic and visual feedback in a collaborative virtual environment , 2007, TCHI.

[38]  Yuanqing Xia,et al.  Robust Sliding-Mode Control for Uncertain Time-Delay Systems Based on Delta Operator , 2009, IEEE Transactions on Industrial Electronics.

[39]  Blake Hannaford,et al.  Control law design for haptic interfaces to virtual reality , 2002, IEEE Trans. Control. Syst. Technol..

[40]  Wei Yu,et al.  Nonlinear control performance assessment in the presence of valve stiction , 2010 .

[41]  C. Karaliotas,et al.  When simulation in surgical training meets virtual reality , 2011 .

[42]  Shih-Tseng Lee,et al.  Development of an Augmented Reality Force Feedback Virtual Surgery Training Platform , 2011 .

[43]  Moharam Habibnejad Korayem,et al.  AFM Based Nano Telemanipulation for Indenting on the Human Chromosomes Using the Sliding Mode Impedance Controller , 2012 .

[44]  Gábor Székely,et al.  Objective Surgical Performance Assessment for Virtual Hysteroscopy , 2007, MMVR.

[45]  Allison M. Okamura,et al.  Friction Compensation for Enhancing Transparency of a Teleoperator With Compliant Transmission , 2007, IEEE Transactions on Robotics.

[46]  Lixu Gu,et al.  Computerized Medical Imaging and Graphics a Hybrid Deformable Model for Real-time Surgical Simulation , 2022 .

[47]  Allison M. Okamura,et al.  Force modeling for needle insertion into soft tissue , 2004, IEEE Transactions on Biomedical Engineering.

[48]  Gábor Székely,et al.  Evaluation of a new virtual-reality training simulator for hysteroscopy , 2009, Surgical Endoscopy.