Proceedings Article10.1109/ICCES.2017.8275277
WeBB: A brain-computer interface web browser based on steady-state visual evoked potentials
Ahmed G. Yehia,Seif Eldawlatly,Mohamed Taher +2 more
- 01 Dec 2017
13
TL;DR: A novel web browser application that utilizes user's Steady-State Visual Evoked Potentials from electroencephalography (EEG) to surf the internet and is demonstrated to be fully functional in web navigation tasks.
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Abstract: Utilizing brain activity to interact with the external environment is no longer impossible thanks to recent advances in developing Brain-Computer Interfaces (BCIs) This paper proposes a novel web browser application that utilizes user's Steady-State Visual Evoked Potentials (SSVEPs) from electroencephalography (EEG) to surf the internet Development of a BCI web browsing application is challenging as it has to provide a comfortable web navigation using an easy-to-use interface, with the highest accuracy of command detection and correct execution In addition, the response time needs to be as small as possible The developed web browser was examined on three healthy subjects using the Emotiv EPOC headset to record EEG signals, and demonstrated to be fully functional in web navigation tasks with an average accuracy across subjects of 8608 ± 1546%
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Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
TL;DR: The physical principles of BCIs, and underlying novel approaches for registration, analysis, and control of brain activity are reviewed, and the new emerging technological trend in the BCI development which consists in using neurointerfaces to improve the interaction between people, so-called brain-to-brain interfaces (BBIs).
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A scoping review on the use of consumer-grade EEG devices for research
Joshua Sabio,Nikolas Williams,Genevieve McArthur,Nicholas A. Badcock +3 more
TL;DR: A scoping review on the use of consumer-grade EEG devices for research found that these devices are widely used in various fields and have a high potential for future research.
A Browser-Driven SSVEP-Based BCI Web Speller
Abdul Saboor,Felix Gembler,Mihaly Benda,Piotr Stawicki,Aya Rezeika,Roland Grichnik,Ivan Volosyak +6 more
- 01 Oct 2018
TL;DR: A browser-driven SSVEP-based BCI web speller that can be used with the help of major existing web browsers is introduced and all the international researchers working in the field of BCI can access this speller online free of charge.
13
Spinning Icons: Introducing a Novel SSVEP-BCI Paradigm Based on Rotation
Maurice Rekrut,Tobias Jungbluth,Jan Alexandersson,Antonio Krüger +3 more
- 14 Apr 2021
TL;DR: In this article, the authors introduce the concept of spinning icons to evoke SSVEPs, where the icons are rotating in a certain frequency around their vertical axis and are supposed to appear more natural and be less stressing for the human eye.
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A Novel Hybrid BCI Web Browser Based on SSVEP and Eye-Tracking
Xinyuan Lin,Wasim Q. Malik,Shaomin Zhang +2 more
- 01 Oct 2019
TL;DR: In this article, a hybrid web browser for neuro-rehabilitation consisting of a web browser following true web access principles was developed and tested using EEG and eye-tracking data.
9
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Brain-computer Interface Based on Visual Evoked Potentials to Command Autonomous Robotic Wheelchair
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Jennifer Mankoff,Anind K. Dey,Udit Batra,Melody M. Moore +3 more
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P300-Based Brain-Computer Interface for Internet Browsing
José L. Sirvent,José M. Azorín,Eduardo Iáñez,Andrés Úbeda,Eduardo Fernández +4 more
- 01 Jan 2010
TL;DR: The implementation of a Brain-Computer Interface (BCI) for controlling Internet browsing that uses electroencephalographic signals to control the computer by evoked potentials through the P300 paradigm and is developed under the BCI2000 platform.
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Design and application of brain-computer interface web browser based on VEP
Jinghai Yin,Derong Jiang,Jianfeng Hu +2 more
- 01 Dec 2009
TL;DR: The article introduces the visual evoked potential-based brain-computer interface for the web browser control, which is the use of fixed-frequency in the monitor blinking objects generated EEG steady-stateVisual evoked it into three control signals, and then as a dedicated webbrowser control information input to achieve use browser's functionality.
17
Principal component analysis-based spectral recognition for SSVEP-based Brain-Computer Interfaces
Ahmed G. Yehia,Seif Eldawlatly,Mohamed Taher +2 more
- 01 Dec 2015
TL;DR: This paper proposes a novel recognition method for Steady-State Visual Evoked Potentials from electroencephalography (EEG) using spectral and time domain filters in order to enhance Signal-to-Noise Ratio (SNR).
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