Frijia, Elisabetta Maria;
(2024)
Advancing Wearable High-Density Diffuse Optical Tomography Technologies and Methods for Infant Functional Neuroimaging.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
The present work describes my contribution to the development, validation and application of a new generation of fibre-less, wearable, high-density diffuse optical tomography technologies that can produce 3D images of human brain function. By undertaking some of the first applications of wearable high-density diffuse optical tomography (HD-DOT), this work goes beyond previous optical neuroimaging studies of the localisation of functional haemoglobin concentration changes in the human brain, with a particularly focus on the infant. The imaging paradigms described in this work combine advancements in ergonomics, cap design, image registration and reconstruction methods to allow mapping of functional responses in infants with high density sampling, and a wide field-of-view. In the first part of this thesis, I describe a study of 4-7 months-old infant brain function using wearable HD-DOT, with an established social stimulus paradigm designed to investigate cognitive and social development. After validating HD-DOT methods in the infant population, I translated these technologies to the neonatal clinic through the development of a further miniaturised, wearable, high-density optical neuroimaging device, designed to monitor neonatal sensorimotor functional development. To validate this technology, a precisely controllable, dynamic, anatomical tissue-mimicking phantom was designed and realised. A comprehensive sensorimotor stimulation paradigm was then developed to enable the examination of healthy and brain-injured infants and to investigate novel imaging markers of motor dysfunction and cerebral palsy. Lastly, to take further advantage of wearable HD-DOT technology, which are increasingly being integrated with motion processing units (MPU), I investigated how motion sensing data can be used in the automated identification of motion artifacts in infant HD-DOT data. This involved the examination of neural network methodologies and machine learning techniques.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Advancing Wearable High-Density Diffuse Optical Tomography Technologies and Methods for Infant Functional Neuroimaging |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10199615 |
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