1 code implementation • 21 Nov 2021 • Jian Cui, Zirui Lan, Tianhu Zheng, Yisi Liu, Olga Sourina, Lipo Wang, Wolfgang Müller-Wittig
For EEG-based drowsiness recognition, it is desirable to use subject-independent recognition since conducting calibration on each subject is time-consuming.
1 code implementation • 30 May 2021 • Jian Cui, Zirui Lan, Yisi Liu, Ruilin Li, Fan Li, Olga Sourina, Wolfgang Mueller-Wittig
Driver drowsiness is one of main factors leading to road fatalities and hazards in the transportation industry.
1 code implementation • 30 May 2021 • Jian Cui, Zirui Lan, Olga Sourina, Wolfgang Müller-Wittig
Results show that the model achieves an average accuracy of 78. 35% on 11 subjects for leave-one-out cross-subject drowsiness recognition, which is higher than the conventional baseline methods of 53. 40%-72. 68% and state-of-the-art deep learning methods of 71. 75%-75. 19%.