Artificial Visual Synapses for Assisting Red‐Green Color Vision Deficiency

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Authors: Haohong Jiang, Yuanhong Hu, Tongzhou Wei, Lixiang Chen, QiaoMing ZHANG, Yanlian Lei
Cited by: 2
References: 31

Abstract

ABSTRACT 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.

Fields of Study & Subjects

Advanced Memory and Neural Computing Photochromic and Fluorescence Chemistry Neural Networks and Reservoir Computing

Publication details

Journal / source
Laser & Photonics Review
Publisher
Wiley
Volume
20
Issue
12
Publication date
13 February 2026
Language
EN