Literature DB >> 23968806

Output control of da Vinci surgical system's surgical graspers.

Paul J Johnson1, David E Schmidt, Umamaheswar Duvvuri.   

Abstract

INTRODUCTION: The number of robot-assisted surgeries performed with the da Vinci surgical system has increased significantly over the past decade. The articulating movements of the robotic surgical grasper are controlled by grip controls at the master console. The user interface has been implicated as one contributing factor in surgical grasping errors. The goal of our study was to characterize and evaluate the user interface of the da Vinci surgical system in controlling surgical graspers.
MATERIALS AND METHODS: An angular manipulator with force sensors was used to increment the grip control angle as grasper output angles were measured. Input force at the grip control was simultaneously measured throughout the range of motion. Pressure film was used to assess the maximum grasping force achievable with the endoscopic grasping tool.
RESULTS: The da Vinci robot's grip control angular input has a nonproportional relationship with the grasper instrument output. The grip control mechanism presents an intrinsic resistant force to the surgeon's fingertips and provides no haptic feedback. The da Vinci Maryland graspers are capable of applying up to 5.1 MPa of local pressure.
CONCLUSIONS: The angular and force input at the grip control of the da Vinci robot's surgical graspers is nonproportional to the grasper instrument's output. Understanding the true relationship of the grip control input to grasper instrument output may help surgeons understand how to better control the surgical graspers and promote fewer grasping errors.
Copyright © 2014 Elsevier Inc. All rights reserved.

Keywords:  Robotic surgery; Usability; User interface; da Vinci

Mesh:

Year:  2013        PMID: 23968806     DOI: 10.1016/j.jss.2013.07.032

Source DB:  PubMed          Journal:  J Surg Res        ISSN: 0022-4804            Impact factor:   2.192


  3 in total

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

Authors:  Chiwon Lee; Yong Hyun Park; Chiyul Yoon; Seungwoo Noh; Choonghee Lee; Youdan Kim; Hee Chan Kim; Hyeon Hoe Kim; Sungwan Kim
Journal:  Med Biol Eng Comput       Date:  2014-11-29       Impact factor: 2.602

Review 2.  Prevalence of haptic feedback in robot-mediated surgery: a systematic review of literature.

Authors:  Farshid Amirabdollahian; Salvatore Livatino; Behrad Vahedi; Radhika Gudipati; Patrick Sheen; Shan Gawrie-Mohan; Nikhil Vasdev
Journal:  J Robot Surg       Date:  2017-12-01

3.  Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions.

Authors:  Lidor Bahar; Yarden Sharon; Ilana Nisky
Journal:  Front Neurorobot       Date:  2020-01-24       Impact factor: 2.650

  3 in total

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