Search · four archives
Search · four archives
19 papers · ranked by Valyu relevance
Zahra Shirzhiyan, Ahmadreza Keihani, Morteza Farahi, Elham Shamsi + 5 more
'Mina GolMohammadi' 'Amin Mahnam' 'Mohsen Reza Haidari' 'Amir Homayoun Jafari' 'Xu Lei'] Code modulated Visual Evoked Potentials (c-VEP) based BCI studies usually employ m-sequences as a modulating codes for their broadband spectrum and correlation property. However, subjective fatigue of the presented codes has been a…
Yonghui Liu, Qingguo Wei, Zongwu Lu, Bin He
The number of selectable targets is one of the main factors that affect the performance of a brain-computer interface (BCI). Most existing code modulated visual evoked potential (c-VEP) based BCIs use a single pseudorandom binary sequence and its circularly shifting sequences to modulate different stimulus targets…
Víctor Martínez-Cagigal, Jordy Thielen, Roberto Hornero, Peter Desain
'Peter Desain'] Research on brain-computer interfaces (BCIs) using the code-modulated evoked potential (c-VEP) has recently achieved remarkable advancements (Martínez-Cagigal et al., [3]). These breakthroughs are attributed to the sophisticated design of the stimulus protocols and the innovative decoding techniques…
Hanneke Scheppink, Rainer Herpers, Jordy Thielen, Ivan Volosyak
A code-modulated motion visual evoked potential (c-MVEP) for brain-computer interfacing (BCI) is presented in this study. This paradigm uses pseudo-random sequences to visually stimulate objects using motion as an alternative to flickering. In an offline experiment of this study, EEG data were recorded and compared…
Milán András Fodor, Atilla Cantürk, Gernot Heisenberg, Ivan Volosyak + 1 more
(1) Background: Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices using electroencephalography (EEG) signals, offering potential applications in assistive technology and neurorehabilitation. Code-modulated visual evoked potential (cVEP)-based BCIs employ…
Kiran Nair, Hubert Cecotti
Non-invasive Brain-Computer Interfaces (BCIs) based on Code-Modulated Visual Evoked Potentials (C-VEPs) require highly robust decoding methods to address temporal variability and session-dependent noise in EEG signals. This study proposes and evaluates several deep learning architectures, including convolutional neural…
K. Cabrera Castillos, S. Ladouce, L. Darmet, F. Dehais
The Steady State Visual Evoked Potential (SSVEP) is a widely used technique in Brain-Computer Interface (BCI) research due to its high information transfer rate. However, this method has some limitations, including lengthy calibration time and visual fatigue. Recent studies have explored the use of code-modulated…
Sebastian Nagel, Martin Spüler
Visual evoked potentials (VEPs) can be measured in the EEG as response to a visual stimulus. Commonly, VEPs are displayed by averaging multiple responses to a certain stimulus or a classifier is trained to identify the response to a certain stimulus. While the traditional approach is limited to a set of predefined…
Sebastian Nagel, Martin Spüler, William Speier
Visual evoked potentials (VEPs) can be measured in the EEG as response to a visual stimulus. Commonly, VEPs are displayed by averaging multiple responses to a certain stimulus or a classifier is trained to identify the response to a certain stimulus. While the traditional approach is limited to a set of predefined…
Runhao Lu, Elizabeth Michael, Catriona L. Scrivener, Jade B. Jackson + 2 more
Selective attention is a fundamental cognitive mechanism that allows people to prioritise task-relevant information while ignoring irrelevant information. Previous research has suggested key roles of parietal evoked potentials like N2pc, and parietal oscillatory responses like alpha power, in spatial attention tasks.…
Nannaphat Siribunyaphat, Yunyong Punsawad, Daniela De Venuto, Sung-Phil Kim
'Sung-Phil Kim'] Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems suffer from low SSVEP response intensity and visual fatigue, resulting in lower accuracy when operating the system for continuous commands, such as an electric wheelchair control. This study proposes two SSVEP…
Harvey Huang, Kendrick N. Kay, Nicholas M. Gregg, Gabriela Ojeda Valencia + 6 more
Electrical stimulation is increasingly used to modulate brain networks for clinical purposes. The basic unit of neurostimulation, a single electrical pulse, can travel through white matter to influence connected neuronal populations. However, the mechanisms by which it influences connected populations is not well…
Bruce C. Hansen, David J. Field, Michelle R. Greene, Cassady Olson + 1 more
Our understanding of information processing by the mammalian visual system has come through a variety of techniques ranging from psychophysics and fMRI to single unit recording and EEG. Each technique provides unique insights into the processing framework of the early visual system. Here, we focus on the nature of the…
Raika Karimi, Arash Mohammadi, Amir Asif, Habib Benali
Recent advancements in Electroencephalography (EEG) sensor technologies and signal processing algorithms have paved the way for further evolution of Brain Computer Interfaces (BCI) in several practical applications ranging from rehabilitation systems to smart consumer technologies. When it comes to Signal Processing…
Nicholas R. Waytowich, Vernon J. Lawhern, Javier O. Garcia, Jennifer Cummings + 3 more
'Jennifer Cummings' 'Josef Faller' 'Paul Sajda' 'Jean M. Vettel'] Objective. Steady-State Visual Evoked Potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs are robust signals measurable in the electroencephalogram (EEG)…
Xianglin Zheng, Zehong Cao, Quan Bai
The new perspective in visual classification aims to decode the feature representation of visual objects from human brain activities. Recording electroencephalogram (EEG) from the brain cortex has been seen as a prevalent approach to understand the cognition process of an image classification task. In this study, we…
Bingchuan Liu, Xinyi Yan, Xiaogang Chen, Yijun Wang + 1 more
There has become of increasing interest in transcranial alternating current stimulation (tACS) since its inception nearly a decade ago. tACS in modulating brain state is an active area of research and has been demonstrated effective in various neuropsychological and clinical domains. In the visual domain, much effort…
Bartu Atabek, Efecan Yilmaz, Cengiz Acartürk, Murat Perit Çakır
—Objective: This paper proposes a novel type of stimulus in the shape of sinusoidal gratings displayed with an imperceptibly high-frequency motion. The stimulus has been designed for use in BCI (Brain Computer Interface) applications that employ visually evoked potentials (VEPs) in an effort to mitigate discomfort…
Arturo Micheli, Davide Consoli, Adrien Merlini, Paolo Ricci + 1 more
'Francesco P. Andriulli'] Abstract— Brain-Computer Interfaces (BCIs) based on Steady State Visually Evoked Potentials (SSVEPs) have proven effective and provide significant accuracy and informationtransfer rates. This family of strategies, however, requires external devices that provide the frequency stimuli required…