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DEVELOPMENT OF SMART CONTACT LENS TO MONITOR EYE CONDITIONS
In this study, we present advancements in smart contact lenses, highlighting their potential as minimally or non-invasive diagnostic and drug delivery platforms. The eyes, rich in physiological and diagnostic data, make contact lens sensors an effective tool for disease diagnosis. These sensors, particularly smart contact lenses, can measure various biomolecules like glucose, urea, ascorbate, and electrolytes (Na+, K+, Cl-, HCO3-) in ocular fluids, along with physical biomarkers such as movement of the eye, intraocular pressure (IOP) and ocular surface temperature (OST).
The study explores the use of continuous, non-invasive contact lens sensors in clinical or point-of-care settings. Although promising, their practical application is hindered by the developmental stage of the field. This thesis addresses these challenges by examining the integration of contact lens sensors, covering their working principle, fabrication, sensitivity, and readout mechanisms, with a focus on monitoring glaucoma and eye health conditions like dry eye syndrome and inflammation.
Our design adapts these sensors to fit various corneal curvatures and thicknesses. The lenses can visually indicate IOP through microfluidic channels' mechanical deformation under ambulatory conditions. We also introduce a colorimetric hydrogel tear fluid sensor that detects pH, electrolytes, and ocular surface temperature, indicating conditions like dry eye disease and inflammation.
The evaluation of these contact lens sensors includes in vivo/vitro biocompatibility, ex vivo functionality studies, and in vivo safety assessments. Our comprehensive analysis aims to enhance the practicality and effectiveness of smart contact lenses in ophthalmic diagnostics and therapeutics.
- Doctor of Philosophy
- Biomedical Engineering
- West Lafayette