Laparoscopic surgery presents practical benefits over traditional open surgery, including reduced risk of infection, discomfort and recovery time for patients. Introducing robot systems into surgical tasks provides additional enhancements, including improved precision, remote operation, and an intelligent software layer capable of filtering aberrant motion and scaling surgical maneuvers. However, the software interface in telesurgery also lends itself to potential adversarial cyber attacks. Such attacks can negatively effect both surgeon motion commands and sensory information relayed to the operator. To combat cyber attacks on the latter, one method to enhance surgeon feedback through multiple sensory pathways is to incorporate reliable, complementary forms of information across different sensory modes. Built-in partial redundancies or inferences between perceptual channels, or perception complementarities, can be used both to detect and recover from compromised operator feedback. In surgery, haptic sensations are extremely useful for surgeons to prevent undue and unwanted tissue damage from excessive tool-tissue force. Direct force sensing is not yet deployable due to sterilization requirements of the operating room. Instead, combinations of other sensing methods may be relied upon, such as noncontact model-based force estimation. This paper presents the design of a surgical simulator software that can be used for vision-based non-contact force sensing to inform the perception complementarity of vision and force feedback for telesurgery. A brief user study is conducted to verify the efficacy of graphical force feedback from vision-based force estimation, and suggests that vision may effectively complement direct force sensing.
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Characterizing Limits of Vision-Based Force Feedback in Simulated Surgical Tool-Tissue Interaction
Haptic feedback can render real-time force interactions with computer simulated objects. In several telerobotic applications, it is desired that a haptic simulation reflects a physical task space or interaction accurately. This is particularly true when excessive applied force can result in disastrous consequences, as with the case of robot-assisted minimally invasive surgery (RMIS) and tissue damage. Since force cannot be directly measured in RMIS, non-contact methods are desired. A promising direction of non-contact force estimation involves the primary use of vision sensors to estimate deformation. However, the required fidelity of non-contact force rendering of deformable interaction to maintain surgical operator performance is not well established. This work attempts to empirically evaluate the degree to which haptic feedback may deviate from ground truth yet result in acceptable teleoperated performance in a simulated RMIS-based palpation task. A preliminary user-study is conducted to verify the utility of the simulation platform, and the results of this work have implications in haptic feedback for RMIS and inform guidelines for vision-based tool-tissue force estimation. An adaptive thresholding method is used to collect the minimum and maximum tolerable errors in force orientation and magnitude of presented haptic feedback to maintain sufficient performance.
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- Award ID(s):
- 2101107
- NSF-PAR ID:
- 10326954
- Date Published:
- Journal Name:
- 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
- Page Range / eLocation ID:
- 4903 to 4908
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/EMBC44109.2020.9176658
