Review of brain-computer interface technology in ophthalmology: Current status, challenges and future directions.

Authors

Jie Zhou, Dongyu Hu, Meichen Wu, Zichao Hong, Rong Li, Qianyin Chen, Xuesong Mi, Jinglin Zhang

Published in

Advances in ophthalmology practice and research. Volume 6. Issue 3. Pages 247-256. Epub Mar 25, 2026.

Abstract

Visual impairment is a major global public health issue. Irreversible blindness caused by end-stage outer retinal diseases, optic nerve injuries, and other conditions remains refractory to conventional therapies. Brain-Computer Interface (BCI) technology, which establishes a direct communication pathway between the brain and external devices, has emerged as a promising interdisciplinary strategy for ophthalmic diagnosis, functional assessment, and artificial visual restoration.
This review summarizes recent advances in BCI technology for ophthalmic applications. In diagnosis and assessment, BCIs provide objective and quantitative measures for evaluating visual disorders and the integrity of the visual pathway through neural signals, using modalities such as steady-state visual evoked potentials, functional near-infrared spectroscopy, and functional magnetic resonance imaging. In treatment, implantable visual prostheses, particularly retinal and cortical prostheses, have shown substantial progress in partial visual reconstruction, while noninvasive BCI-related approaches are being increasingly explored for rehabilitation. However, major barriers remain, including difficulties in signal acquisition, immature encoding and decoding algorithms, limited electrode array performance, inefficient wireless transmission, implantation-related complications, high device costs, and insufficient evidence for some noninvasive interventions. Legal, regulatory, and ethical concerns also constrain large-scale clinical implementation.
BCI technology holds considerable promise in ophthalmology, but significant technical and translational challenges remain. Future advances in artificial intelligence, flexible electronics, virtual reality, wireless systems, and closed-loop strategies are expected to improve precision, safety, adaptability, and accessibility, thereby enabling more effective diagnostic and visual rehabilitation solutions for patients with severe visual impairment.

PMID:
42572548
Bibliographic data and abstract were imported from PubMed on 10 Aug 2026.

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