A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is
IEEE transactions on neural systems and rehabilitation engineering
Driver vigilance estimation is an important task for transportation safety. Wearable and portable brain-computer interface devices provide a powerful means for real-time monitoring of the vigilance level of drivers to help with avoiding distracted or impaired driving. In this paper, we propose a novel multimodal architecture for in-vehicle vigilance estimation from Electroencephalogram and Electrooculogram. To enable the system to focus on the most salient parts of the learned multimodaldoi:10.1109/tnsre.2021.3089594 pmid:34129500 arXiv:1912.07812v4 fatcat:4raxianeiveapgepvfvqgzx2mi