|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kathia Chenane, Youcef Touati, Larbi Boubchir and Boubaker Daachi
The following contribution describes a neural net-based, noninvasive methodology for electroencephalographic (EEG) signal classification. The application concerns a brain?computer interface (BCI) allowing disabled people to interact with their environmen...
ver más
|
|
|
|
|
|
|
|
|
|
|
Boris Medina Salgado, Leonardo Duque Muñoz
Pág. 9 - 19
AbstractDownloadsReferencesHow to Cite
|
|
|
|
|
|
|
|
|
|
|
Boris Medina Salgado, Leonardo Duque Muñoz
Abstract AuthorsDownloadsReferencesHow to Cite
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chiara Suraci, Sara Pizzi, Federico Montori, Marco Di Felice and Giuseppe Araniti
The pandemic caused by COVID-19 has shed light on the urgency of bridging the digital divide to guarantee equity in the fruition of different services by all citizens. The inability to access the digital world may be due to a lack of network infrastructu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ba-Viet Ngo and Thanh-Hai Nguyen
A semi-automatic wheelchair allows disabled people to possibly control in an indoor environment with obstacles and targets. The paper proposes an EEG-based control system for the wheelchair based on a grid map designed to allow disabled people to reach a...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Feng Tian, Yan Zhang and Yingjie Li
Focusing on virtual reality (VR) and film cutting, this study compared and evaluated the effect of visual mode (2D, VR) and cutting rate (fast, medium, slow) on a load, to make an attempt for VR research to enter the cognitive field. This study uses a 2 ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Giulia Bressan, Giulia Cisotto, Gernot R. Müller-Putz and Selina Christin Wriessnegger
The classification of different fine hand movements from electroencephalogram (EEG) signals represents a relevant research challenge, e.g., in BCI applications for motor rehabilitation. Here, we analyzed two different datasets where fine hand movements (...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mashael Aldayel, Mourad Ykhlef and Abeer Al-Nafjan
This article presents an application of deep learning in preference detection performed using EEG-based BCI.
|
|
|
|
|
|
|
|
|
|
|
Hongquan Qu, Zhanli Fan, Shuqin Cao, Liping Pang, Hao Wang and Jie Zhang
Electroencephalogram (EEG) signals contain a lot of human body performance information. With the development of the brain?computer interface (BCI) technology, many researchers have used the feature extraction and classification algorithms in various fiel...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hikaru Sato and Yoshikazu Washizawa
A brain-computer interface (BCI) is a tool to communicate with a computer via brain signals without the user making any physical movements, thus enabling disabled people to communicate with their environment and with others. P300-based ERP spellers are a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Christoph Reichert, Stefan Dürschmid, Rudolf Kruse and Hermann Hinrichs
Brain?computer interfacing (BCI) is a promising technique for regaining communication and control in severely paralyzed people. Many BCI implementations are based on the recognition of task-specific event-related potentials (ERP) such as P300 responses. ...
ver más
|
|
|
|
|
|