Earlier detection of glaucoma from Aqueous humor fluid of human eye Through spintronic sensor and Machine learning algorithms

Abstract

Glaucoma is an eye disease in human, which leads to vision loss. Vision loss occurs in human eye, when the glaucoma is untreated or undiagnose at earlier stage. The detection of glaucoma at earlier stage is a challenging task due to less symptoms. Moreover, glaucoma symptoms are overlapping with other eye disease symptoms such as myopia, headache, and red eye. Glaucoma classify as open angle and close angle glaucoma. Glaucoma arise due to static and dynamic nature of aqueous humor fluid in eye at canal of schlemm. In Open Angle Glaucoma (OAG), excess Aqueous Humor (AH) fluid pass to schlemm canal and high dynamic in nature. Whereas for Closed Angle Glaucoma (CAG), AH fluid in schlemm canal is static nature. Glaucoma measure through Intra Ocular Pressure (IOP). newlineDifferent instruments for measuring glaucoma are Goldmann tonometry, pneumotonometry, applanation tonometry and dynamic contour tonometry, which measures Intra Ocular Pressure (IOP) of eye. High IOP damages the optic nerve, cup and disc of eye. However, above instruments never detects the glaucoma at earlier stage due to minimal change in IOP of eye. The IOP of normal eye is between 12 to 22 mmHg. Researchers developed IOP measurement through implantable sensor such as strain gauge, pressure transducer, wireless IOP transducer, optical sensor to measure IOP and non-invasive methods such as (i) ophthalmoscopy for observing optic nerve, retina, (ii) perimetry for measuring peripheral vision of eye, and (iii) gonioscopy for visualization of angle between iris and cornea. However, earlier detection of glaucoma still remains as a challenge to researchers. newline