Electroencephalography signal processing based on textural features for monitoring the driver's state by a Brain-Computer Interface

• URL: http://arxiv.org/abs/2010.06412v2
• Date: Sat, 17 Oct 2020 14:46:00 GMT
• Title: Electroencephalography signal processing based on textural features for monitoring the driver's state by a Brain-Computer Interface
• Authors: Giulia Orr\`u, Marco Micheletto, Fabio Terranova, Gian Luca Marcialis
• Abstract summary: We investigate a textural processing method as an indicator to estimate the driver's vigilance in a hypothetical Brain-Computer Interface (BCI) system. The novelty of the solution proposed relies on employing the one-dimensional Local Binary Pattern (1D-LBP) algorithm for feature extraction from pre-processed EEG data. Our analysis allows to conclude that the 1D-LBP adoption has led to significant performance improvement.
• Score: 3.613072342189595
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this study we investigate a textural processing method of electroencephalography (EEG) signal as an indicator to estimate the driver's vigilance in a hypothetical Brain-Computer Interface (BCI) system. The novelty of the solution proposed relies on employing the one-dimensional Local Binary Pattern (1D-LBP) algorithm for feature extraction from pre-processed EEG data. From the resulting feature vector, the classification is done according to three vigilance classes: awake, tired and drowsy. The claim is that the class transitions can be detected by describing the variations of the micro-patterns' occurrences along the EEG signal. The 1D-LBP is able to describe them by detecting mutual variations of the signal temporarily "close" as a short bit-code. Our analysis allows to conclude that the 1D-LBP adoption has led to significant performance improvement. Moreover, capturing the class transitions from the EEG signal is effective, although the overall performance is not yet good enough to develop a BCI for assessing the driver's vigilance in real environments.

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