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Georgios Prapas, Kosmas Glavas, Katerina D. Tzimourta, Alexandros T. Tzallas and Markos G. Tsipouras
Brain-computer interfaces (BCIs) are becoming an increasingly popular technology, used in a variety of fields such as medical, gaming, and lifestyle. This paper describes a 3D non-invasive BCI game that uses a Muse 2 EEG headband to acquire electroenceph...
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Rito Clifford Maswanganyi, Chungling Tu, Pius Adewale Owolawi and Shengzhi Du
Transfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used to address the challenges of cross-session ...
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Diego F. Collazos-Huertas, Andrés M. Álvarez-Meza and German Castellanos-Dominguez
Brain activity stimulated by the motor imagery paradigm (MI) is measured by Electroencephalography (EEG), which has several advantages to be implemented with the widely used Brain?Computer Interfaces (BCIs) technology. However, the substantial inter/intr...
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Dawid Pawus and Szczepan Paszkiel
This article is a continuation and extension of research on a new approach to the classification and recognition of EEG signals. Their goal is to control the mobile robot through mental commands, using a measuring set such as Emotiv Epoc Flex Gel. The he...
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Woo-Sung Choi and Hong-Gi Yeom
A brain?computer interface (BCI) is a promising technology that can analyze brain signals and control a robot or computer according to a user?s intention. This paper introduces our studies to overcome the challenges of using BCIs in daily life. There are...
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Andrea Sanna, Federico Manuri, Jacopo Fiorenza and Francesco De Pace
Human?robot collaboration (HRC) is a new and challenging discipline that plays a key role in Industry 4.0. Digital transformation of industrial plants aims to introduce flexible production lines able to adapt to different products quickly. In this scenar...
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Grégoire Cattan, Anton Andreev and Etienne Visinoni
The integration of a P300-based brain?computer interface (BCI) into virtual reality (VR) environments is promising for the video games industry. However, it faces several limitations, mainly due to hardware constraints and limitations engendered by the s...
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Feng Li, Xiaoyu Li, Fei Wang, Dengyong Zhang, Yi Xia and Fan He
Aiming at enhancing the classification accuracy of P300 Electroencephalogram signals in a non-invasive brain?computer interface system, a novel P300 electroencephalogram signals classification algorithm is proposed which is based on improved convolutiona...
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Mashael Aldayel, Mourad Ykhlef and Abeer Al-Nafjan
This article presents an application of deep learning in preference detection performed using EEG-based BCI.
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Steven Galindo-Noreña, David Cárdenas-Peña and Álvaro Orozco-Gutierrez
Brain?computer interface (BCI) systems communicate the human brain and computers by converting electrical activity into commands to use external devices. Such kind of system has become an alternative for interaction with the environment for people suffer...
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