US 12,358,370 B2
Closed-loop real time SSVEP-based heads-up display to control in vehicle features using deep learning
Hossein Hamidi Shishavan, New Britain, CT (US); Insoo Kim, Avon, CT (US); Mohammad Behzadi, Storrs, CT (US); Ercan Dede, Ann Arbor, MI (US); and Danny Lohan, Ann Arbor, MI (US)
Assigned to Toyota Motor Engineering & Manufacturing North America, Inc., Plano, TX (US); and University of Connecticut Health Center, Farmington, CT (US)
Filed by Toyota Motor Engineering & Manufacturing North America, Inc., Plano, TX (US); and University of Connecticut Health Center, Farmington, CT (US)
Filed on Dec. 16, 2022, as Appl. No. 18/067,473.
Prior Publication US 2024/0198798 A1, Jun. 20, 2024
Int. Cl. B60K 35/00 (2024.01); A61B 5/00 (2006.01); A61B 5/372 (2021.01); B60K 35/10 (2024.01); B60K 35/23 (2024.01); B60K 35/29 (2024.01); G06N 3/0464 (2023.01)
CPC B60K 35/00 (2013.01) [A61B 5/372 (2021.01); A61B 5/725 (2013.01); A61B 5/7257 (2013.01); A61B 5/7267 (2013.01); G06N 3/0464 (2023.01); B60K 35/10 (2024.01); B60K 35/23 (2024.01); B60K 35/29 (2024.01); B60K 2360/119 (2024.01); B60K 2360/149 (2024.01); B60K 2360/188 (2024.01)] 20 Claims
OG exemplary drawing
 
1. A vehicle system, comprising a controller programmed to:
display a plurality of icons on a heads-up-display (HUD) of a vehicle;
receive electroencephalography (EEG) data from a driver of the vehicle;
perform a Fast Fourier Transform (FFT) of the EEG data to obtain an EEG spectrum;
input the EEG spectrum into a trained machine learning model that outputs a prediction of an icon that the driver is looking at based on the EEG spectrum;
determine which of the plurality of icons the driver is viewing based on the output of the trained machine learning model; and
perform one or more vehicle operations based on the output of the trained machine learning model.