Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 85-91). / Measuring the mechanical properties of soft tissue can be an important method to detect pathology. Concerning the brain in particular, correlation between abnormal tissue stiffness and morbidity has been reported for Alzheimer's disease, Parkinson's disease and brain tumors, among others. On a more fundamental level, the nature and behavior of the brain from a mechanical standpoint is relatively understudied, in comparison to those from the chemical, electromagnetic and optical perspective. Current techniques fall into two main categories: one establishes direct contact to measure the deformation of tissue under various mechanical loads, the other solves the inverse problem based on the tissue displacement data collected through a number of imaging modalities. Both categories, however, have their limitations in providing ideal mechanical measurement of the brain, ranging from form factor compatibility, spatiotemporal resolution and accuracy. In this light, this work aims at developing an implantable measurement device that can bypass these limitations and provide in situ, in vivo, real-time, long-term monitoring of soft tissue biomechanics. The initial goal is to create a functional sensor front-end that can differentiate materials of different stiffness. As this project is to continue beyond the thesis, this thesis will present the current development progress, issues encountered and corresponding counter-measures, and discuss the prospective work in the future. / by Zijun Wei. / S.M.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/119090 |
| Date | January 2018 |
| Creators | Wei, Zijun, S.M. Massachusetts Institute of Technology |
| Contributors | Canan Dagdeviren., Program in Media Arts and Sciences (Massachusetts Institute of Technology), Program in Media Arts and Sciences (Massachusetts Institute of Technology) |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 91 pages, application/pdf |
| Rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582 |
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