# The BCI (Brain Computer Interface) Glaucoma Study: Objective Home-Based Detection of Progressive Visual Function Loss in Glaucoma

> **NIH NIH R01** · DUKE UNIVERSITY · 2020 · $561,010

## Abstract

PROJECT SUMMARY
Glaucoma is the leading cause of irreversible blindness and visual impairment in the world. As the disease
generally remains asymptomatic until late stages, early detection of functional damage is paramount, so that
treatment can be initiated or advanced in order to avoid progression to disability. Detection of functional loss is
traditionally made with standard automated perimetry (SAP). However, SAP testing is limited by subjectivity of
patient responses and large variability, requiring a large number of tests for detection of change over time. These
tests are conducted in clinic-based settings and, due to limited patient availability and health care resources,
insufficient tests are usually acquired over time, resulting in delayed detection of progression. The requirement
for highly trained technicians, cost, complexity, and lack of portability of SAP also preclude its use for screening
of visual field loss in underserved populations. To address shortcomings of current methods to assess visual
function, we have developed an innovative brain-computer interface (BCI) that allows portable and objective
assessment of visual function loss through multifocal steady-state visual-evoked potentials (mfSSVEP). The BCI
consists of a wearable device employing a head-mounted display (HMD) integrated with wireless
electroencephalography (EEG). In cross-sectional investigations, we demonstrated that the BCI mfSSVEP
parameters were able to successfully detect glaucomatous damage with excellent test-retest repeatability. Based
on the encouraging results of the preliminary studies, we now propose a multicenter investigation of the ability
of longitudinal BCI mfSSVEP parameters in detecting glaucoma progression. In Specific Aim 1, we will collect
longitudinal BCI mfSSVEP data during clinic-based visits in glaucoma patients and healthy subjects. We
hypothesize that BCI mfSSVEP data will be able to successfully detect progression and measure rates of change,
as compared to functional assessment by SAP and structural assessment by optical coherence tomography. In
Aim 2, we will collect home-based longitudinal mfSSVEP data and investigate their performance for detecting
glaucoma progression and measuring rates of change. We hypothesize that the increased frequency of testing
from home-based BCI testing will result in earlier detection and prediction of progression compared to clinic-
based data and conventional testing. In Aim 3, we will investigate the ability of BCI mfSSVEP data in predicting
patient-reported quality of life in glaucoma. In summary, this proposal employs a highly innovative BCI device to
acquire longitudinal mfSSVEP data with the central aim of improving detection and prediction of glaucoma
progression. The approach has the potential to address major current limitations of standard testing, significantly
impacting management of the disease. Objective home-based testing of visual function could represent a
transformative way of diag...

## Key facts

- **NIH application ID:** 9881308
- **Project number:** 5R01EY029885-02
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** SANJAY ASRANI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $561,010
- **Award type:** 5
- **Project period:** 2019-03-01 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9881308

## Citation

> US National Institutes of Health, RePORTER application 9881308, The BCI (Brain Computer Interface) Glaucoma Study: Objective Home-Based Detection of Progressive Visual Function Loss in Glaucoma (5R01EY029885-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9881308. Licensed CC0.

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