THESIS
2019
xiii, 90 pages : illustrations (some color) ; 30 cm
Abstract
A double coil contact lens sensor (CLS) was designed to continuously monitor human
intraocular pressure (IOP). The double coil contact lens sensor (CLS) could track the corneal
curvature change and human eye environment noise by using 2 embedded passive
inductor-capacitor (LC) resonators. The CLS signal could be affected by IOP, ocular
movement or eye tissue dielectric influence etc. Due to the complexity of the human eye
environment, correlation of the CLS frequency signals and IOP is studied on a model eye
testing platform, in order to perform accurate IOP predictions based on CLS signals.
In this thesis, a silicone eye testing platform was designed to provide a similar environment
to a human eye, and to ensure minimal variation. When the CLS was being applied on the
silicone...[
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A double coil contact lens sensor (CLS) was designed to continuously monitor human
intraocular pressure (IOP). The double coil contact lens sensor (CLS) could track the corneal
curvature change and human eye environment noise by using 2 embedded passive
inductor-capacitor (LC) resonators. The CLS signal could be affected by IOP, ocular
movement or eye tissue dielectric influence etc. Due to the complexity of the human eye
environment, correlation of the CLS frequency signals and IOP is studied on a model eye
testing platform, in order to perform accurate IOP predictions based on CLS signals.
In this thesis, a silicone eye testing platform was designed to provide a similar environment
to a human eye, and to ensure minimal variation. When the CLS was being applied on the
silicone eye, a post lens tear film could be formed. The CLS could move smoothly on the
silicone eye, as with a human eye. CLS was tested on the silicone eye, and the change of
resonant frequencies is correlated with both the change in silicone eye radius of curvature
and IOP, with different magnitudes. The relationship between CLS frequency signals and
silicone eye IOP was studied and recorded.
An IOP prediction program was developed to predict human IOP with input of a human trial
CLS frequency signals by using a database of the silicone eye. Results showed that
maximum prediction error of human IOP is ±10.4 mmHg. The relationship of CLS frequency
signals and human IOP was studied and found.
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