Assessments of functional loss and of structural damage to the optic nerve are typical evaluations per-formed in the diagnosis and monitoring of glaucoma. This proposal aims at developing the hardware systemthat will allow acquisition of fundus photographs using the nGoggle, a portable Brain-Computer Interface (BCI)which integrates a wearable, wireless, electroencephalogram (EEG) system and a head-mounted display tomonitor electrical brain activities associated with visual field stimulation. In a previous project, we developed thenGoggle portable system for the assessment of visual function deficits in order to address limitations of standardautomated perimetry (SAP), a traditional but subjective visual field test. We compared the diagnostic accuraciesof the nGoggle and SAP in discriminating patients with glaucoma from healthy subjects and found that the BCIperformed at least as well, if not better than SAP, with the additional advantage of portability and objectivity. With rapid advancements in smartphone cameras, it is now possible to develop compact auto-focusingfundus cameras and integrate them into our neuro-monitoring nGoggle. Recently we developed an approachnamed Machine-to-Machine (M2M), a deep learning algorithm that was trained to analyze fundus photos andpredict quantitative measurements of retinal nerve fiber layer thickness and neuroretinal rim provided by spectraldomain-optical coherence tomography (SDOCT), with high correlation and agreement with the original SDOCTobservations. This approach opens up the possibility of using simple fundus photographs to extract quantitativeinformation about neural damage in glaucoma. By combining functional assessment currently provided by thenGoggle with structural assessment capability, this new system would result in a very unique device capable ofportable structural and functional assessment of optic nerve damage for a multitude of eye conditions, not limitedto glaucoma, such as age-related macular degeneration, retinal degenerations and non-glaucomatous optic neu-ropathies. The specific aims of this Phase I SBIR project are (1) to incorporate a high-resolution auto-focusingfundus camera to the nGoggle head-mounted display in full compliance with ophthalmic instrument safety stand-ards and fundus camera functional standards, and (2) to demonstrate the ability of the nGoggle fundus camerato capture high-quality optical nerve images from a model eye. Successful development of this system will enableboth structural and functional assessments of retinal conditions to be performed easily and inexpensively usinga portable device.
Public Health Relevance Statement: PROJECT NARRATIVE
NGoggle Inc. proposes to develop a new wearable ophthalmic diagnostic instrument capable of performing con-
current structural and functional assessment to diagnose and monitor optic neuropathies and retinal diseases.
This project aims at developing a pair of compact high-resolution fundus cameras in full compliance with oph-
thalmic instrument safety standards and integrating them into our neuro-monitoring nGoggle, an instrument with
the demonstrated capability of estimating functional vision loss in glaucoma patients based on their electroen-
cephalogram (EEG) responses evoked by visual stimuli. We also intend to demonstrate that the optic nerve
images of model eyes taken by the integrated fundus cameras can yield consistent and compatible cup-to-disc
ratios when compared with the measurements obtained from the same model eyes using optical coherence
tomography (OCT). After successful demonstration, we plan to conduct clinical tests in the subsequent phase of
this project.
Project Terms: Algorithms ; Anatomy ; Anatomic ; Anatomic Sites ; Anatomic structures ; Anatomical Sciences ; Diagnosis ; Disease ; Disorder ; Electroencephalography ; EEG ; Visual evoked cortical potential ; Visual Evoked Potentials ; Visual Evoked Response ; Eye ; Eyeball ; Glaucoma ; glaucomatous ; Light ; Photoradiation ; Names ; Nerve ; Optic Nerve ; Cranial Nerve II ; Second Cranial Nerve ; optic nerve disorder ; Cranial Nerve II Diseases ; Cranial Nerve II Disorder ; Neural-Optical Lesion ; Optic Nerve Diseases ; Optic Neuropathy ; Second Cranial Nerve Diseases ; second cranial nerve disorder ; Optics ; optical ; Patients ; Perimetry ; Publications ; Scientific Publication ; Resources ; Research Resources ; Retina ; Retinal Degeneration ; degenerative retina diseases ; retina degeneration ; retinal degenerative ; retinal degenerative diseases ; Retinal Diseases ; Retinal Disorder ; retina disease ; retina disorder ; retinopathy ; Safety ; Testing ; Time ; Vision ; Sight ; visual function ; Visual impairment ; Diminished Vision ; Low Vision ; Partial Sight ; Reduced Vision ; Subnormal Vision ; vision impairment ; visually impaired ; Visual Fields ; eye field ; Healthcare ; health care ; base ; Fundus photography ; eye fundus photography ; fundus camera ; Clinical ; Phase ; Series ; Evaluation ; Training ; disability ; brain electrical activity ; Age related macular degeneration ; Age-Related Maculopathy ; age related macular dystrophy ; senile macular disease ; Measurement ; instrument ; Diagnostic ; Pulse ; Physiologic pulse ; Clinic ; Source ; System ; vision loss ; visual loss ; Blindness ; gaze ; early detection ; Early Diagnosis ; field based data ; field learning ; field test ; field study ; Performance ; visual stimulus ; Accuracy of Diagnosis ; diagnostic accuracy ; hazard ; neural ; relating to nervous system ; Structure ; Agreement ; Devices ; Fundus ; Modeling ; portability ; Doppler OCT ; OCT Tomography ; optical Doppler tomography ; optical coherence Doppler tomography ; Optical Coherence Tomography ; Cell Phone ; Cellular Telephone ; iPhone ; smart phone ; smartphone ; Cellular Phone ; Thickness ; Thick ; preventing ; prevent ; Address ; Detection ; Reproducibility ; Resolution ; Flare ; Small Business Innovation Research Grant ; SBIR ; Small Business Innovation Research ; Wireless Technology ; wireless ; Monitor ; Development ; developmental ; Electroencephalogram ; Image ; imaging ; cost ; brain computer interface ; Imaging technology ; innovation ; innovate ; innovative ; loss of function ; functional loss ; retinal nerve fiber layer ; RNFL ; Systems Development ; screening ; wearable device ; wearable electronics ; wearable technology ; patient response ; patient specific response ; responsive patient ; retinal imaging ; retina imaging ; deep neural network ; deep learning based neural network ; deep learning neural network ; deep neural net ; deep learning ; neural network algorithm ; deep learning algorithm ; head mounted display ; head mounted device ; detection test ; detection tests ; nerve damage ;
