Toyota Motor Engineering & Manufacturing North America, Inc.

University of Connecticut

Kia Golzari

Muhamed K Farooq

Insoo Kim

Hossein Hamidi Shishavan

Ercan Mehmet Dede

In accordance with one embodiment of the present disclosure, a method includes measuring brain activity for a target frequency and a second harmonic frequency based on a default value of display parameters for a plurality of icons, determining whether a strength of the target frequency and the second harmonic frequency are below a threshold level, and modifying one or more display parameters in response to the strength of the target frequency and the second harmonic frequency being below the threshold level.

Methods, systems, and non-transitory computer-readable mediums for SSVEP detection optimization

In accordance with one embodiment of the present disclosure, a method includes generating a plurality of icons, wherein each icon has a target frequency unique from each other, receiving brain activity data based on an epoch, generating a reference signal based on the epoch, calculating correlation coefficients between the brain activity data and the reference signal, wherein the correlation coefficients are calculated in a window that is within ±0.5 Hz of the target frequencies, including endpoints, determining a confidence score based on the correlation coefficients and the epoch, and determining a selected icon among the plurality of icons based on the correlation coefficients in response to the confidence score surpassing a threshold confidence score.

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Vernon, CT, United States of America

Kia Golzari