The retina encompasses several cone and rod photoreceptors at fovea region i.e., 90 million cells of rod photoreceptors and 4.5million cells of cone photoreceptors. The overall photoreceptors determine the vision of every human. An electromagnetic dielectric resonator antenna has been presented for retina photoreceptors in order to model them at fovea and its peripheral retina with the respected angular spectrum. Three coloring primary system of human eye (R, G, B) can be realized based on the model. Three miscellaneous models i.e., simple, graphene coated, and interdigital models have been presented in this paper. The nonlinear property of interdigital structures is one of the best advantages to use for creating the capacitor. The capacitance property helps improving the upper band of visible spectrum. The absorption of light for graphene as an energy harvesting material and its conversion into electrochemical signals is making it one of the best models. The mentioned three electromagnetic models of human photoreceptors have been expressed as a receiver antenna. The proposed electromagnetic models based on dielectric resonator antenna (DRA) are being analyzed for cones and rods photoreceptors of retina in the human eye by Finite Integral Method (FIM) utilized by CST MWS. The results show that the models are so fine for vision spectrum due to its localized near field enhancement property. The results indicate fine parameters of (return loss below -10 dB) with invaluable resonants in a wide range of frequencies from 405 THz to 790 THz (vision spectrum), appropriate (insertion loss 3-dB bandwidth), very good field distribution of electric and magnetic fields for flowing the power and electrochemical signals. Finally, mfERG clinical and experimental results validate the numeric results by the normalized output to input ratio of these models and it points out that these models can stimulate the electrochemical signals in photoreceptor cells for the best suiting of realizing the new retinal implants.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988474PMC
http://dx.doi.org/10.1016/j.heliyon.2023.e13794DOI Listing

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