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Micromachined multifunctional polyvinylidene fluoride tactile sensor for minimally invasive surgery graspers

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Micromachined multifunctional polyvinylidene fluoride tactile sensor for minimally invasive surgery graspers

Sokhanvar, Saeed (2007) Micromachined multifunctional polyvinylidene fluoride tactile sensor for minimally invasive surgery graspers. PhD thesis, Concordia University.

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Abstract

Promising results of Minimally Invasive Surgery, MIS, in the last two decades have been the main incentive of numerous researches in this area. However, despite numerous advantages of this relatively new technique, using of long tools inserted through small ports on the body deprive surgeons of the depth perception, dexterity, sense of touch, and straightforward hand-eye coordination that are accustomed to surgeons in open procedures. Many researches have been launched to rectify the mentioned shortcomings and some improvements, such as, excellent stereo visual feedback and satisfactory dexterity, have been made recently in robotic assisted surgical systems. However, the current MIS tools whether in endoscopic surgery or in robotic assisted surgery are incapable of providing tactile feedback. The tactile information collected by the surgeon's hand in an open surgery is vital for success in complex and delicate operations. For instance, the ability to distinguish between different types of tissue in the body is of vital importance to a surgeon. Before making an incision into tissue, the surgeon must identify what type of tissue is being incised. Failure to classify properly the tissue can cause severe consequences. There have been some attempts to develop smart MIS graspers with integrated sensors. However, many of these integrated sensors are limited to force or softness sensing. From a functional point of view, integrating several sensors each of them is responsible for measuring a specific quantity is difficult. In contrast, a multi-functional tactile sensor which would be able to address several concerns such as force measurement, determining position of the force, assessing softness of the grasped object, detecting any hidden lumps in bulk soft tissue is highly desirable. The transduction techniques used in the relevant researches have been reported as capacitive and piezoelectric techniques. In this study, the piezoelectric polymer Polyvinylidene Fluoride (PVDF) has been used as the transducer due to its unique features and also bio-compatibility. This study aimed at introducing a multi-functional tactile sensor which would be able to address many of the required information in a surgery procedure. A unit of the proposed sensor is able to measure the applied force and its position along the length of the sensor system. In addition, it is also able to differentiate the softness of the contact objects. An array of sensor is able to locate the applied load or any hidden mass in a plane (i.e. xy plane). Integration of the sensors into both jaws of the grasper, enables the smart grasper to determine the depth of any hidden masses. Regardless of the type of the integrated sensor, the study of stress profile in the presence of a lump, at the contact surface of object-grasper is of importance. The behavior of the soft tissue highly influences the stress distribution at the contact surface of tissue and grasper. Although modeling all of the complex behavior of soft tissue is very difficult, in this study, the nonlinear characteristics of the tissue is considered. In the absence of the soft tissue the simulation and experiments are conducted on the elastomers which exhibit very similar behavior. However, the ultimate objective is the integration of the proposed sensor with the existing MIS graspers. To do this, the sensor must be microfabricated. Therefore, in order to study the feasibility of micromachining of the proposed sensor, the microfabrication procedure for the tactile sensor was examined and the fabrication difficulties were identified. The conventional anisotropic wet etching has been used for micromachining the device.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (PhD)
Authors:Sokhanvar, Saeed
Pagination:xxiii, 220 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:Ph. D.
Program:Mechanical and Industrial Engineering
Date:2007
Thesis Supervisor(s):Packirisamy, M
ID Code:975454
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:08
Last Modified:18 Jan 2018 17:40
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