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Neurophysiological mental fatigue assessment for developing user-centered Artificial Intelligence as a solution for autonomous driving.
Front Neurorobot
November 2023
BrainSigns SRL, Rome, Italy.
The human factor plays a key role in the automotive field since most accidents are due to drivers' unsafe and risky behaviors. The industry is now pursuing two main solutions to deal with this concern: in the short term, there is the development of systems monitoring drivers' psychophysical states, such as inattention and fatigue, and in the medium-long term, there is the development of fully autonomous driving. This second solution is promoted by recent technological progress in terms of Artificial Intelligence and sensing systems aimed at making vehicles more and more accurately aware of their "surroundings.
View Article and Find Full Text PDFTemporal and spectral electrooculographic features in a discrete precision task.
Psychophysiology
March 2024
School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK.
This study aimed to evaluate the utility and applicability of electrooculography (EOG) when studying ocular activity during complex motor behavior. Due to its lower spatial resolution relative to eye tracking (ET), it is unclear whether EOG can provide valid and accurate temporal measurements such as the duration of the Quiet Eye (QE), that is the uninterrupted dwell time on the visual target prior to and during action. However, because of its greater temporal resolution, EOG is better suited for temporal-spectral decomposition, a technique that allows us to distinguish between lower and higher frequency activity as a function of time.
View Article and Find Full Text PDF[Automatic removal algorithm of electrooculographic artifacts in non-invasive brain-computer interface based on independent component analysis].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
December 2022
Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding, Hebei 071002, P. R. China.
The non-invasive brain-computer interface (BCI) has gradually become a hot spot of current research, and it has been applied in many fields such as mental disorder detection and physiological monitoring. However, the electroencephalography (EEG) signals required by the non-invasive BCI can be easily contaminated by electrooculographic (EOG) artifacts, which seriously affects the analysis of EEG signals. Therefore, this paper proposed an improved independent component analysis method combined with a frequency filter, which automatically recognizes artifact components based on the correlation coefficient and kurtosis dual threshold.
View Article and Find Full Text PDFEOG-Based Gaze Angle Estimation Using a Battery Model of the Eye.
Annu Int Conf IEEE Eng Med Biol Soc
July 2019
In this work, a novel method to estimate the gaze angles using electrooculographic (EOG) signals is presented. Specifically, this work investigates the use of a battery model of the eye, which relates the recorded EOG potential with the distances between the corresponding electrode and the centre points of the cornea and retina, for gaze angle estimation. Using this method a cross-validated horizontal and vertical gaze angle error of 2.
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