A grip force model for the da Vinci end-effector to predict a compensation force

A torque transfer system (TTS) that measures grip forces is developed to resolve a potential drawback of the current da Vinci robot system whose grip forces vary according to the different postures of its EndoWrist. A preliminary model of EndoWrist Inner Mechanism Model (EIMM) is also developed and validated with real grip force measurements. EndoWrist’s grip forces, posture angles, and transferred torque are measured by using TTS. The mean measured grip forces of three different EndoWrist for 27 different postures were very diverse. The EndoWrist exerted different grip forces, with a minimum of 1.84-times more and a maximum of 3.37-times more in specific posture even if the surgeon exerted the same amount of force. Using the posture angles as input and the grip forces as output, the EIMM is constructed. Then, expected grip force values obtained from EIMM are compared with actual measurements of da Vinci EndoWrist to validate the proposed model. From these results, surgeons will be beneficial with the understandings of actual grip force being applied to tissue and mechanical properties of robotic system. The EIMM could provide a baseline in designing a force-feedback system for surgical robot. These are significantly important to prevent serious injury by maintaining a proper force to tissue.

[1]  C. A. Mosse,et al.  Device for measuring the forces exerted on the shaft of an endoscope during colonoscopy , 1998, Medical and Biological Engineering and Computing.

[2]  Darren George,et al.  SPSS for Windows Step by Step: A Simple Guide and Reference , 1998 .

[3]  Paul J Johnson,et al.  Output control of da Vinci surgical system's surgical graspers. , 2014, The Journal of surgical research.

[4]  Makoto Hashizume,et al.  A new era of robotic surgery assisted by a computer-enhanced surgical system. , 2002, Surgery.

[5]  Tobias Ortmaier,et al.  Cartesian control issues for minimally invasive robot surgery , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[6]  Bernhard Kübler,et al.  Prototype of Instrument for Minimally Invasive Surgery with 6-Axis Force Sensing Capability , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[7]  G. Boyle.  Review of the (1985) Standards for educational and psychological testing: AERA, APA and NCME. , 1987 .

[8]  Jenny Dankelman,et al.  Indirect measurement of pinch and pull forces at the shaft of laparoscopic graspers , 2012, Medical & Biological Engineering & Computing.

[9]  G. Sung,et al.  Robotic laparoscopic surgery: a comparison of the DA Vinci and Zeus systems. , 2001, Urology.

[10]  Elspeth M McDougall,et al.  Differences in grip forces among various robotic instruments and da Vinci surgical platforms. , 2011, Journal of endourology.

[11]  Rajni V. Patel,et al.  Haptic interaction in robot‐assisted endoscopic surgery: a sensorized end‐effector , 2005, The international journal of medical robotics + computer assisted surgery : MRCAS.

[12]  Catherine E. Lewis,et al.  Tactile Feedback Induces Reduced Grasping Force in Robot-Assisted Surgery , 2009, IEEE Transactions on Haptics.

[13]  Sung Yul Park,et al.  Intraoperative breakage of needle driver jaw during robotic-assisted laparoscopic radical prostatectomy. , 2008, Urology.

[14]  Vincent Hayward,et al.  Measurement, Analysis, and Display of Haptic Signals During Surgical Cutting , 2002, Presence: Teleoperators & Virtual Environments.

[15]  D. Gravel,et al.  Maximal grip force in chronic stroke subjects and its relationship to global upper extremity function , 1999, Clinical rehabilitation.