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A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
Published on: July 7, 2023
Review of brain-computer interface technology in ophthalmology: Current status, challenges and future directions
Jie Zhou1, Dongyu Hu1, Meichen Wu1
1Department of Ophthalmology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Advances in Ophthalmology Practice and Research
|August 10, 2026
Summary
Brain-Computer Interface (BCI) technology offers new hope for vision restoration in ophthalmology. While promising for diagnosis and treatment, challenges in technology and implementation must be overcome for widespread clinical use.
Area of Science:
- Ophthalmology
- Neuroscience
- Biomedical Engineering
Background:
- Visual impairment is a global health concern with limited treatment options for irreversible blindness.
- Brain-Computer Interface (BCI) technology presents a novel interdisciplinary approach for ophthalmic applications.
- BCI facilitates direct brain-device communication for diagnosis, assessment, and visual restoration.
Purpose of the Study:
- To review recent advancements in BCI technology for ophthalmic applications.
- To highlight BCI's role in diagnosing visual disorders and assessing visual pathway integrity.
- To discuss BCI's potential in visual prostheses and rehabilitation strategies.
Main Methods:
- Review of current BCI technologies in ophthalmology.
- Analysis of diagnostic modalities using neural signals (e.g., steady-state visual evoked potentials, fNIRS, fMRI).
- Evaluation of implantable visual prostheses (retinal and cortical) and noninvasive BCI rehabilitation approaches.
Main Results:
- BCIs provide objective, quantitative measures for visual disorder assessment.
- Implantable visual prostheses show progress in partial visual reconstruction.
- Noninvasive BCI approaches are increasingly explored for visual rehabilitation.
Conclusions:
- BCI technology holds significant promise for ophthalmology but faces technical and translational hurdles.
- Challenges include signal acquisition, algorithm immaturity, electrode performance, and cost.
- Future advancements in AI, flexible electronics, and VR are crucial for effective BCI-based visual solutions.
