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Real-Time Vision-Based Approach for Estimating Contact Forces on Soft Tissues, with Applications to Laparoscopic surgery

Kohani, Mehdi | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44000 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering Department
  6. Advisor(s): Farahmand, Farzam; Behzadipour, Saeed
  7. Abstract:
  8. Lack of force feedback during minimally invasive procedures is one of the downsides of such interventions and might result to excessive damage to surrounding tissues. The goal of the present research is to introduce a vision-based approach to estimate contact forces on soft tissues. In this approach, a model was developed in which, image of deformation of a sample soft tissue, under the jaws of laparoscopic gripper, is the input and the output is the gripper force.
    In this method, using finite element simulation, a database from different deformations of a rectangular soft tissue was generated. Accordingly, from the geometric position of nodes of the upper surface of the soft tissue, 3 distinct geometric features from 2D deformation and 4 distinct features from 3D deformation data, were extracted. Then, two multilayer perceptron neural networks (for 2d and 3D deformation) were trained from these features and corresponding gripper force (computed from finite element simulation). Neural network results showed that contact force can be estimated with 94% accuracy.
    Practicability of the proposed algorithm was verified by performing 2D and 3D deformation experiments on Paraffin Gel samples. Experimental results showed that for deformations less than 20% of the initial size of the specimen, gripper force can be estimated with more than 20% accuracy
  9. Keywords:
  10. Feature Extraction ; Finite Element Analysis ; Multilayered Neural Network ; Soft Tissues Deformation ; Force Feedback

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