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Novel low-cost device for accurate, non-invasive IOP monitoring using a mobile phone

Background

Glaucoma is a heterogenous group of eye diseases caused by increases in intraocular pressure (IOP) that damage the optic nerve. It is the second leading cause of blindness globally and the leading cause of irreversible blindness. Global estimates of the prevalence of glaucoma were 76 million in 2020 and this is expected to increase to 111.8 million by 2040. The effects of glaucoma are gradual and progress undetected. Vision loss from glaucoma is irreversible so early detection and continuous monitoring are essential to slow the progression of disease. Goldmann applanation tonometry (GAT) is the gold standard for monitoring IOP levels. The challenge with this technique is that it requires local anesthetic, it must be performed by a trained professional and only a few readings are obtained annually. The IOP is known to fluctuate throughout the day and is impacted by several factors including changes in heart rate and body position. Additionally, the shape of the eye changes with changing IOP and this can be exploited to develop novel IOP monitoring tools. These facts support the need for an at home IOP monitoring system that provides longitudinal data. Continuous monitoring devices that accurately detect IOP fluctuations, can detect glaucoma, track its progression, and allow a more individualized therapeutic response.

Technology Overview

Queen’s researchers have developed multiple novel designs of soft contact lensesfor continuous measurement of IOP. These designs are protected by two separate patent applications with two granted US patents off the initial patent application. One set of designs contains strain-amplifying microchannels, closed or open to the atmosphere, which contain an indicator solution partially filling the microchannel. As IOP changes it alters the contact lens and causes the indicator to move through the microchannel and these changes are captured by smartphone camera. These changes are quantified by AI and accurately reflect the IOP in mmHg. The other design includes microstructures/markers in the lenses which deform in response to changes in the curvature of the lens as a result of changes in IOP. The distance between two or more markers or a change in the size and shape of a marker can be captured in digital images at two or more time periods. These changes correspond to changes in IOP.

Both contact lenses will be worn throughout the day and will be used with a smartphone camera to take images of the contact lens periodically. Machine learning algorithms in the smartphone app capture changes in the microchannel fluid and provide an absolute IOP value using (1)change in IOP in mmHg or (2)the ratio of x length and y length of contact lens microstructures. Information can be read at any time of day in either an upright or reclined position.