Artificial Visual Synapses for Assisting Red-Green Color Vision Deficiency

Color vision is essential for human perception, yet red-green color vision deficiency (CVD) affects millions and poses significant challenges for chromatic discrimination. Existing assistive technologies are often static and distort true color perception. In this study, we introduce a novel photo-synaptic device designed to enhance chromatic discrimination for individuals with red-green CVD by converting photonic signals into digital synaptic currents. Utilizing a poly(3-hexylthiophene) (P3HT)-based organic heterojunction, our device achieves a tenfold improvement in wavelength discrimination between red and green light compared to a control device that mimics red-green color blindness. When integrated with artificial neural networks, the device demonstrates a remarkable 92% accuracy in recognizing complex chromatic patterns. Our findings further demonstrate the device's potential to enhance color recognition for individuals with color weakness, enabling more effective differentiation of intricate patterns. This work provides a robust solution for enhancing color perception and lays the groundwork for next-generation bioelectronic systems focused on sensory restoration.