Robust algorithms for analysis of traveling wave motions of the tectorial membrane
Author(s)
Filizzola Ortiz, Roberto Daniel.
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Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Dennis M. Freeman.
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The tectorial membrane is a gelatinous matrix in the cochlea that is essential for the amplification and decomposition of sound in mammalian hearing. Material properties of the tectorial membrane have been studied in vitro by measuring the decay and speed of artificially generated waves of motion in excised cochlea. Optical systems for measuring subnanometer motion are essential in these experiments. Analysis of data from these systems typically requires human intervention, which limits the objectivity and precision of the results. To overcome these limitations, this thesis focuses on the development of robust algorithms for analysing traveling wave motion data with minimal human intervention. First, we analyse a general purpose framework to estimate wave motions along a parametric path that is selected by a user. Although not fully automatic, this method is more flexible, faster, and less prone to error than previous methods. Second, we present a new gradient-based, fully automatic algorithm for estimating wave motions. Although it achieves high accuracy in synthetic data, systematic errors result when it is used to analyze images from some physiological experiments. Finally, we expand the traditional tectorial membrane model by including effects of wave reflection. This model improves the accuracy of wave estimates in experimental data and also provides convincing fits to data that were previously dismissed because the motions did not demonstrate monotonic decay. The new model demonstrates that the non-monotonicity is due to interference between the forward traveling wave and its reflection.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020 Cataloged from the official PDF of thesis. Includes bibliographical references (pages 51-52).
Date issued
2020Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.