Control Design and Task Performance in Endoscopic Teleoperation

Ori Ben-Porat, Moshe Shoham, Joachim Meyer

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Endoscopic surgery, while offering considerable gains for the patient, has created new difficulties for the surgeon. One problem is the fulcrum effect which causes the movement of a surgical instrument, as seen on the monitor, to be in the opposite direction to the movement of the surgeon's hand. The problem has been shown to impede the acquisition of endoscopic skills. Teleoperated robotic arms may circumvent this problem by allowing different control-response relations. Four alternative control designs of a teleoperated device were compared in a simulated endoscopic task. A rigid teleoperated robotic arm with two degrees of freedom representing a surgical tool was coupled to a joystick in a position control mode. Feedback was provided through a video display. Participants without prior experience in endoscopy performed a target acquisition task, first by pointing the robotic arm at the targets, and later by maneuvering an object. Performance was measured under four different combinations of visual-motor mapping (normal/reversed), and the joystick's orientation (upwards/ downwards). Task completion time under normal visual-motor mapping was found to be significantly shorter than under reversed visual-motor mapping, emphasizing the potential advantage of a teleoperated endoscopic system. The joystick's orientation affected the maneuvering of an object under only the reversed visual-motor mapping, implying that the positioning of a surgical tool and the manipulation of tissues or objects with the tool may be differentially affected by the control design.

Original languageEnglish
Pages (from-to)256-267
Number of pages12
JournalPresence: Teleoperators and Virtual Environments
Issue number3
StatePublished - 1 Jan 2000

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition


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