Abstract
The way towards the next generation of visual cortical prosthesis is visualised through an engineering cycle based on a cybernetic paradigm. Our proposal is to develop a configurable and wearable system that will generate simulated prosthetic vision, while on the other hand, perform intracortical stimulation when applied to blind patients, so that it is expected that improvements with sighted volunteers, in combination with transformed reality strategies, will correlate with similar improvements in blind patients. The resulting cybernetic model involves modelling from stimuli to visual percepts, and in parallel, developing the best suited transformed reality strategy leading to a better perception of the environment. Deep learning approaches for object detection, monocular depth estimation, or structural edge detection, in combination with the use of an eye-tracking system, will lead to an integrated system that has proved to be wearable, optimised, modular, and computationally lightweight. To assess the cybernetic approach, behavioural experiments are proposed using two different scenarios. Firstly, a corridor with a series of obstacles and a controlled but more complex environment that resembles a city square, called StreetLab.
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Acknowledgements
This project has received funding by grant RTI2018-098969-B-100 from the Spanish Ministerio de Ciencia Innovación y Universidades, by grant PROMETEO/2019/119 from the Generalitat Valenciana (Spain), by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 861423 (enTRAIN Vision) and by grant agreement No. 899287 (project NeuraViPer).
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Val Calvo, M. et al. (2022). Horizon Cyber-Vision: A Cybernetic Approach for a Cortical Visual Prosthesis. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications. IWINAC 2022. Lecture Notes in Computer Science, vol 13258. Springer, Cham. https://doi.org/10.1007/978-3-031-06242-1_38
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