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Felipe A Medeiros, John K Zao, Yute Wang, Masaki Nakanishi, Yuan-Pin Lin, Alberto Diniz-Filho, Tzyy-Ping Jung; The nGoggle: A Portable Brain-Based Method for Assessment of Visual Function Deficits in Glaucoma. Invest. Ophthalmol. Vis. Sci. 2016;57(12):3940.
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© ARVO (1962-2015); The Authors (2016-present)
To describe the development of a new portable objective method for assessment of functional deficits in glaucoma. The device is armed with electrophysiological sensors, mA current stimulators and wireless fog/cloud computing support to enable portable and objective assessment of visual field defects using multifocal steady-state visual-evoked potentials (mfSSVEPs).
A prototype has been developed by adding the following sensors, actuators and processors to a Samsung Gear VR Goggle (Figure 1): Six EEG dry electrodes at Oz, O3, O4, Pz, left and right mastoids with the Reference at Fz; Three EEG/EOG/EMG electrodes at FPz and the inner corners of lower eyelids; Dual-band 602.11 a/b/g/n Wi-Fi and Bluetooth 4.0 radios; Dual-core processor running Yocto Linux with Preempt-RT patch. Artifact removal, spectral and canonical correlation analyses can be run in the embedded processor in near real time. Gaussian pseudo-random current noise of ±1mA can be injected through four electrodes at Fz, Oz, left and right mastoids. The frontend device is supported by a pervasive computing infrastructure consisting of near-end fog servers and far-end cloud computing centers. EOG captured around the perimeters of subjects’ eyes was used to monitor the dynamics of eye saccade and fixation losses. Multiple frequency-tagged flickering sectors (alternating black/white) are presented in order to elicit mfSSVEP signals. All sectors flickered concurrently at frequencies from 8 to 11.8 Hz with a step of 0.2 Hz.
Figure 2 shows the waveforms and power spectra of EEG/EOG signals (10 Sec epochs) collected in an experimental subject using the prototype, indicating reliable capture of mfSSVEP and EOG signals.
In initial development and experimental testing, the system was able to reliably capture and analyze visually induced-mfSSVEP signals and electrooculogram signals on the fly. The portability and wireless cloud-based signal transmission capability may enable in-home and remote objective testing of visual function deficits with this system.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.
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