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Alexey Kozin, Anton Gerasimov, Maxim Bakaev, Anton Pashkov and Olga Razumnikova
Brain?computer interfaces (BCIs) based on steady-state visually evoked potentials (SSVEPs) are inexpensive and do not require user training. However, the highly personalized reaction to visual stimulation is an obstacle to the wider application of this t...
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Dmitry Lazurenko, Igor Shepelev, Dmitry Shaposhnikov, Anton Saevskiy and Valery Kiroy
A linear discriminant analysis transformation-based approach to the classification of three different motor imagery types for brain?computer interfaces was considered. The study involved 16 conditionally healthy subjects (12 men, 4 women, mean age of 21....
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David Balderas, Pedro Ponce, Diego Lopez-Bernal and Arturo Molina
Education 4.0 is looking to prepare future scientists and engineers not only by granting them with knowledge and skills but also by giving them the ability to apply them to solve real life problems through the implementation of disruptive technologies. A...
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Hyung Seok Nam, Han Gil Seo, Ja-Ho Leigh, Yoon Jae Kim, Sungwan Kim and Moon Suk Bang
This study is an investigation of the practical demands of potential users of assistive rehabilitation robots from a survey performed in patients with functional upper limb impairments. While the development of simple and practical robots is becoming mor...
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Andrey N. Afonin,Rustam G. Asadullaev,Maria A. Sitnikova,Andrey R. Gladyshev,Kamil Kh. Davletchurin
The review describes the main principles as well as advantages and disadvantages of the modern brain-computer interfaces applied in robotic devices. The invasive and non-invasive devices based on the origin of a signal, invasiveness and location of probe...
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Katerina D. Tzimourta, Ioannis Tsoulos, Thanasis Bilero, Alexandros T. Tzallas, Markos G. Tsipouras and Nikolaos Giannakeas
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Sepideh Kilani, Seyedeh Nadia Aghili and Mircea Hulea
A new approach is introduced to address the subject dependency problem in P300-based brain-computer interfaces (BCI) by using transfer learning. The occurrence of P300, an event-related potential, is primarily associated with changes in natural neuron ac...
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Egor I. Chetkin, Sergei L. Shishkin and Bogdan L. Kozyrskiy
Bayesian neural networks (BNNs) are effective tools for a variety of tasks that allow for the estimation of the uncertainty of the model. As BNNs use prior constraints on parameters, they are better regularized and less prone to overfitting, which is a s...
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Yuhang Gao, Juanning Si, Sijin Wu, Weixian Li, Hao Liu, Jianhu Chen, Qing He and Yujin Zhang
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Samira Muhammad Ismail,Paulo Victor de Oliveira Miguel,Gilmar Barreto
Pág. pp. 11 - 16
A new electronic learning device generation can be created from a new paradigm in human sense and efferent resources. The brain computer interfaces (BCI) with ECOLIG protocol can be used to get the advantages from â??Near To Eye
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Mashael Aldayel, Amira Kharrat and Abeer Al-Nafjan
Individual choices and preferences are important factors that impact decision making. Artificial intelligence can predict decisions by objectively detecting individual choices and preferences using natural language processing, computer vision, and machin...
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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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Wallace Moreira Bessa and Gabriel da Silva Lima
Memristive neuromorphic systems represent one of the most promising technologies to overcome the current challenges faced by conventional computer systems. They have recently been proposed for a wide variety of applications, such as nonvolatile computer ...
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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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Aqsa Shakeel, Toshihisa Tanaka and Keiichi Kitajo
Neural oscillations are vital for the functioning of a central nervous system because they assist in brain communication across a huge network of neurons. Alpha frequency oscillations are believed to depict idling or inhibition of task-irrelevant cortica...
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Eduardo Carabez, Miho Sugi, Isao Nambu and Yasuhiro Wada
As brain-computer interfaces (BCI) must provide reliable ways for end users to accomplish a specific task, methods to secure the best possible translation of the intention of the users are constantly being explored. In this paper, we propose and test a n...
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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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Marcin Kolodziej, Andrzej Majkowski, Remigiusz J. Rak and Przemyslaw Wiszniewski
One approach employed in brain?computer interfaces (BCIs) involves the use of steady-state visual evoked potentials (SSVEPs). This article examines the capability of artificial intelligence, specifically convolutional neural networks (CNNs), to improve S...
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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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Saraswati Sridhar and Vidya Manian
Cognitive deterioration caused by illness or aging often occurs before symptoms arise, and its timely diagnosis is crucial to reducing its medical, personal, and societal impacts. Brain?computer interfaces (BCIs) stimulate and analyze key cerebral rhythm...
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