Processing math: 100%
Alertness Estimation Using Connection Parameters of the Brain Network | IEEE Journals & Magazine | IEEE Xplore

Alertness Estimation Using Connection Parameters of the Brain Network


Abstract:

Alertness mechanism of unmanned monitoring vehicles to environment is important. Especially, the vigilance modeling of underground security robots has a particularly sign...Show More

Abstract:

Alertness mechanism of unmanned monitoring vehicles to environment is important. Especially, the vigilance modeling of underground security robots has a particularly significance because the underground is a dangerous environment. However, there is no a mature methodology for the alertness computation. In this work, four parts of the alertness estimation are focused. First, an autonomous robot alertness mechanism framework is proposed by using the deep reinforcement learning model of the human alertness mechanism. Second, a fast K-T filtering algorithm is developed to eliminate the multiple noises of the electroencephalograph (EEG) signals by the blind source separation and the adjustable Q factor wavelet transform. Third, the description problem of the directed interaction stability of the cortical EEG signals is solved by the ensemble empirical mode decomposition and the directional transfer function. Fourth, the human alertness estimation is explored by using the support vector regression of the dynamically spatial-temporal brain network connection parameters. Experiments show that, the mean square error and the determination coefficient of the explored alertness estimation are respectively 0.115 and 0.8337. Compared with the scalp EEG alertness estimation, it has a better performance because the mean square error is decreased by 0.0684, and the determination coefficient is increased by 0.023.
Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: 23, Issue: 12, December 2022)
Page(s): 25448 - 25457
Date of Publication: 09 November 2021

ISSN Information:

Funding Agency:


Contact IEEE to Subscribe

References

References is not available for this document.