Tactile Feedback in Minimally Invasive Robotic Surgery with the Use of Strain Gauges
AuthorGovalla, Dema Nua
AdvisorRozenblit, Jerzy W.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThe ability to perceive tactile feedback in minimally invasive robotic surgery (MIRS) is beneficial for a surgeon in the operation room. Surgeons benefit from tactile feedback because it grants them the ability to obtain the object and environmental information. In MIRS, this will contribute to a surgeon being able to feel organ tissue hardness and softness, evaluate anatomical structures, and measure tissue properties. Consequently, giving the surgeon tactile feedback enhances the efficiency and safety of performing robotic surgery by decreasing vital organ tissue damage and tissue trauma. Unfortunately, there is currently no commercial system that implements such feedback in MIRS. This paper proposes a method for surgeons to acquire tactile feedback during surgery, specifically detecting tissues or organs’ deformation. The technique used consists of two strain gauges that are installed to the outer jaws of scissors forceps. This prototype is used to replicate the jaw of a robotic instrument grasper similar to the one used on the state-of-the-art da Vinci Surgical System. The strain gauges are then used to detect the softness and hardness by closing the prototype’s jaws and measuring three attributes used to differentiate between an object’s hardness. The attributes are used to build the software design, a fuzzy classification system (FCS). The FCS classification system is used to classify objects into five different deformation categories: very soft, soft, medium, hard, and very hard. The FCS is tested using testing data to prove that the proposed method is feasible.
Degree ProgramGraduate College
Electrical & Computer Engineering