Large scale retinal modeling for the design of new generation retinal prostheses

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Tran, Trung Kien (2015) Large scale retinal modeling for the design of new generation retinal prostheses. PhD thesis, University of Nottingham.

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Abstract

With the help of modern technology, blindness caused by retinal diseases such as age-related macular degeneration or retinitis pigmentosa is now considered reversible. Scientists from various fields such as Neuroscience, Electrical Engineering, Computer Science, and Bioscience have been collaborating to design and develop retinal prostheses, with the aim of replacing malfunctioning parts of the retina and restoring vision in the blind. Human trials conducted to test retinal prostheses have yielded encouraging results, showing the potential of this approach in vision recovery. However, a retinal prosthesis has several limitations with regard to its hardware and biological functions, and several attempts have been made to overcome these limitations.

This thesis focuses on the biological aspects of retinal prostheses: the biological processes occurring inside the retina and the limitations of retinal prostheses corresponding to those processes have been analysed. Based on these analyses, three major findings regarding information processing inside the retina have been presented and these findings have been used to conceptualise retinal prostheses that have the characteristics of asymmetrical and separate pathway stimulations. In the future, when nanotechnology gains more popularity and is completely integrated inside the prosthesis, this concept can be utilized to restore useful visual information such as colour, depth, and contrast to achieve high-quality vision in the blind.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Maul, Tomas
Bargiela, Andrzej
Subjects: Q Science > QA Mathematics > QA 75 Electronic computers. Computer science
R Medicine > RE Ophthalmology
Faculties/Schools: University of Nottingham, Malaysia > Faculty of Science and Engineering — Science > School of Computer Science
Item ID: 29175
Depositing User: TRAN, TRUNG KIEN
Date Deposited: 08 Sep 2015 08:59
Last Modified: 15 Dec 2017 23:04
URI: https://eprints.nottingham.ac.uk/id/eprint/29175

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