Abstract
Visual field defects often go unnoticed by patients, making early diagnosis especially important. However, the commonly used Standard Automated Perimetry (SAP) assessment relies on manual user input. As such, we consider utilizing Steady-State Visual Evoked Potential (SSVEP) to provide accurate and objective results. We believe that SSVEP can produce more reliable data than SAP, given the same conditions. To test this, we created an SSVEP based program with the same layout as an existing SAP program. Subjects were then tested with both programs under two conditions—blocked and unblocked vision. SSVEP data was collected using a portable Brain Computer Interface and processed using canonical-correlation analysis. We constructed contour plots of the visual field for all sets of data, allowing us to easily compare the two methods. SAP ended up being more accurate than SSVEP, but SSVEP managed to approximate the visual field fairly well. A paired-samples t-test indicated that there was no significant difference in the Canonical-Correlation Coefficient values for blocked and unblocked visual fields (p = 0.492). We hope that our work can encourage greater development for SSVEP-based visual field assessment. In the future, we can use SSVEP for each stimulus at the same time but at different frequencies, allowing testing time to be cut down threefold. Another realm of inquiry would be the use of Virtual Reality to present the SSVEP stimuli, creating a completely portable diagnostic system.
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Tan, Y.Y.V., Njondimackal, D.J., Phyo Wai, A.A. (2021). Empirical Evaluation of Perimetry and Electrophysiology Methods in Visual Field Assessment. In: Guo, H., Ren, H., Kim, N. (eds) IRC-SET 2020. Springer, Singapore. https://doi.org/10.1007/978-981-15-9472-4_39
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DOI: https://doi.org/10.1007/978-981-15-9472-4_39
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