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A Step-by-Step Tutorial for a Motor Imagery–Based BCI
Published in Chang S. Nam, Anton Nijholt, Fabien Lotte, Brain–Computer Interfaces Handbook, 2018
Hohyun Cho, Minkyu Ahn, Moonyoung Kwon, Sung Chan Jun
It is important to consider the line noise when recording EEG data. A signal power of 50–60 Hz line noise (220 or 110 V, respectively) is much higher than neural oscillation. Although software solutions exist to remove the line noise (e.g., notch filtering), data acquisition hardware that uses DC can reduce the line noise much more than can systems that use alternating current, for example, battery-based hardware. Therefore, we recommend a DC system. Hardware engineers in the BCI field are interested in developing wireless, dry electrode, tripolar concentric electrode, or multimodal EEG to study more accurate and convenient uses of BCI (Ahn et al. 2016; Besio et al. 2006; Cincotti et al. 2006; Nguyen et al. 2016). We believe that the most important issue in software engineering is saving data with correct trigger information and using EEG to study accurate, single-trial–based, and real-time experiments. The literature (Wolpaw and Wolpaw 2012) includes representative types of software for MI experiments: BCI2000 (Schalk et al. 2004), OpenVibe (Renard et al. 2010), and BCILAB (Kothe and Makeig 2013).
Measurements and Assessment of Lighting Parameters and Measures of Non-Visual Effects of Light
Published in Agnieszka Wolska, Dariusz Sawicki, Małgorzata Tafil-Klawe, Visual and Non-Visual Effects of Light, 2020
Agnieszka Wolska, Dariusz Sawicki, Małgorzata Tafil-Klawe
The EEG technique is mostly used as a practical method to investigate the alertness state from the registered EEG signals of the human brain. EEG fluctuations apparently arise from simultaneous changes in brain mechanisms controlling central arousal and alertness and in the levels of coherent neural activity at several characteristic neural oscillation frequencies. The relationship between changes in performance and the EEG spectrum during sleepiness makes it possible to make practical use of an EEG-based real-time alertness estimation as an effect of light exposure.
A Functional BCI Model by the P2731 working group: Physiology
Published in Brain-Computer Interfaces, 2021
Ali Hossaini, Davide Valeriani, Chang S. Nam, Raffaele Ferrante, Mufti Mahmud
We mentioned that Hans Berger described alpha and beta waves, also called neural oscillations, in his 1929 report on EEG. Thus, neural oscillations have been studied during the entire history of BCI, and, in the popular imagination, they are one of the primary physiological correlates with mental activity. Neural oscillations are created by large numbers of neurons firing in synchrony. Associations with the broadly drawn psychological states charted below are still valid, but neural oscillations are now recognized as signals that coordinate activities across the brain. Section 5 will introduce some of these new horizons.