Graduation Semester and Year
2023
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Mechanical Engineering
Department
Mechanical and Aerospace Engineering
First Advisor
Panayiotis S. Shiakolas
Abstract
Identification of tissue viscoelastic properties could provide valuable information for assessing its healthiness or disease state. Current technologies present challenges to access and perform localized tissue assessment in confined spaces in the human body through contact indentation/palpation. As such, there is a need for a diagnostic system capable of measuring tissue relaxation response at the local site by accessing the tissue through a natural orifice. This dissertation presents a strain gauge-based uniaxial micro-force sensor, part of the aforementioned system, capable of measuring tissue response data in confined human space environments. A sensing system design methodology is developed and presented. The sensor operational requirements are used to define design specifications and constraints. An exhaustive search discrete optimization approach is formulated, and finite element analysis is employed to identify optimal sensor component design values. A micro-force sensor with an overall diameter of approximately 3.5mm was prototyped and characterized. Characterization test beds were developed in-house to evaluate the performance of the prototyped micro-force sensor using experimentally collected equivalent force data. The performance of the sensor as it relates to its load-bearing capacity, resolution, sensitivity, accuracy, precision, repeatability error, and hysteresis were evaluated to be 1.07N, 0.13mN, 859.7 μϵ/N , ±28.6mN, 87.2% (23mN), ±3.13% (±25mN), and 118mN respectively. The characterized micro-force sensor was subsequently employed to perform in vivo tissue characterization experiments on the human forearm through normal contact palpation at different control indentation depths and indentation rates according to approved Institutional Review Board protocol 2023-0306. Tissue characterization experiments were performed on 30+ participants ranging in age (20 to 79 years old), race (Asian, Caucasian, Others), gender (male, female), and arm strength training (exercise) or not. A three-element Maxwell-Wiechert viscoelastic model, commonly used for soft tissue characterization, was employed to evaluate the viscoelastic parameters of instantaneous shear modulus and relaxation time constant. The analysis of the results showed that the tissue became compliant as one aged. No identifiable differences were observed for the viscoelastic properties of the tissue as a function of race. The result revealed that females exhibited relatively stiffer tissue. Individuals associated with arm strength training had stiffer tissue. The experimental results provide confidence to employ the sensor to distinguish healthy from diseased tissue in vivo. The dissertation concludes with the importance of this research as a component of a diagnostic system along with a discussion on future research direction.
Keywords
Medical diagnostic device, Micro-force sensor, Design, Optimization, Characterization, Prototype, Tissue characterization
Disciplines
Aerospace Engineering | Engineering | Mechanical Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Kumat, Shashank S., "On the Development of a Sensing System Methodology to Evaluate the Viscoelastic Properties of Soft Tissues as a Means of Disease Prognosis" (2023). Mechanical and Aerospace Engineering Dissertations. 245.
https://mavmatrix.uta.edu/mechaerospace_dissertations/245
Comments
Degree granted by The University of Texas at Arlington