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We investigate the neural correlates of visual working memory using electroencephalography (EEG). Our objective is to develop a cognitive Brain-Computer Interface (BCI) able to monitor visual working memory load in real-time. A system with these properties would eventually have different applications, such as training, rehabilitation, or safety while operating dangerous machinery. The BCI performances...
This paper demonstrates a high performance brain-computer interface (BCI) that allows users to dial phone numbers. The system is based on Canonical Correlation Analysis (CCA) and Steady-State Visual Evoked Potential (SSVEP). Through six buttons (9Hz, 10Hz, 11Hz, 12Hz, 13 Hz, 14Hz) displayed on the screen, subjects can choose the number by gazing at the computer interface. This proposed EEG (Electroencephalography)...
This paper presents a brain-computer interface (BCI) in which the face paradigm was optimized for the visual mismatch negativity (MMN). There were 12 cells in a LCD monitor. A single letter was at the bottom of each cell. In the new paradigm, a color face appeared above each of the 12 cells randomly while the gray faces appeared in others 11 cells. A traditional face paradigm with single character...
We aim to develop a brain-machine interface (BMI) system that estimates user's gaze or attention on an object to pick it up in the real world. In Experiment 1 and 2 we measured steady-state visual evoked potential (SSVEP) using luminance and/or contrast modulated flickers of photographic scenes presented on a head-mounted display (HMD). We applied multiclass SVM to estimate gaze locations for every...
We investigated whether listener-assisted scanning, an alternative communication method for persons with severe motor and visual impairments but preserved cognitive skills, could be used for spelling with EEG. To that end spoken letters were presented sequentially, and the participants made selections by performing motor execution/imagery or a cognitive task. The motor task was a brisk dorsiflexion...
Non-invasive Brain-Computer Interface (BCI) has appeared as a new hope for a large population of disabled people, who were waiting for a new communication means that would translate some brain responses into actions. After several decades of research in fields such as neuroscience and machine learning, the performance remains too low due to the low signal to noise ratio of the EEG signal, and the...
Brain machine interfaces (BMIs) transform modulation of electroencephalogram (EEG) elicited by cognitive and mental events users voluntarily perform into words and commands in accordance with their intents to communicate with somebody else or machines the users want to control. One of the leading paradigms in BMIs includes a method which utilizes the modulation of a steady state visual evoked potentials...
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to realize high-speed communication between the human brain and the external environment. Recently, multiple access (MA) methods in telecommunications have been introduced into the system design of BCIs and showed their potential in improving BCI performance. This study investigated the feasibility of...
In this paper we describe a multiplayer brain-computer interface (BCI) based on the classic game of checkers using steady-state visually evoked potentials (SSVEPs). Previous research in BCI gaming focuses mainly on the production of software-based games using a computer screen — few hardware-based BCI games using a physical board have been developed. Hardware-based games can present a unique set of...
In applying mental imagery brain-computer interfaces (BCIs) to end users, training is a key part for novice users to get control. In general learning situations, it is an established concept that a trainer assists a trainee to improve his/her aptitude in certain skills. In this work, we want to evaluate whether we can apply this concept in the context of event-related desynchronization (ERD) based,...
Multimodal spellers combining visual and auditory stimulation have recently gained more attention in ERP-based Brain-Computer Interfaces (BCIs). Most studies found an improved efficiency compared to unimodal paradigms while few have explored the effect of the visual-to-auditory delays on the spelling performance. Here, we study five conditions with different visual-to-auditory delays, in order to...
This paper presents a comparison between two different technologies of acquisition systems (BrainNet36 and Emotiv Epoc) for an Independent-BCI based on Steady-State Visual Evoked Potential (SSVEP). Two stimuli separated by a viewing angle < 1° were used. Multivariate Synchronization Index (MSI) technique was used as feature extractor and five subjects participated in the experiments. The class...
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to provide a fast communication channel between human brain and external devices. In SSVEP-based BCIs, Canonical Correlation Analysis (CCA) has been widely used to detect frequency-coded SSVEPs due to its high efficiency and robustness. However, the detectability of SSVEPs differs among frequencies due...
We present an automated solution for the acquisition, processing and classification of electroencephalography (EEG) signals in order to remotely control a remotely located robotic hand executing communicative gestures. The Brain-Computer Interface (BCI) was implemented using the Steady State Visual Evoked Potential (SSVEP) approach, a low-latency and low-noise method for reading multiple non-time-locked...
In recent years it has been shown to be possible to create a Brain Computer Interface (BCI) using non-invasive electroencephalographic (EEG) measurements of covert visual spatial attention. For example, that both Steady-State Visual Evoked Potentials (SSVEP) and parieto-occipital alpha band activity have been shown to be sensitive to covert attention and this has been exploited to provide simple communication...
In recent years, based on the steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs) have generated significant interest, due to their shorter calibration times and higher information transfer rates. Target identification is the core signal processing task in BCIs. Power spectral density analysis (PSDA) and canonical correlation analysis (CCA) are the most popular and widely...
Interferences from the spatially adjacent non-target stimuli evoke ERPs during non-target sub-trials and lead to false positives. This phenomenon is commonly seen in visual attention based BCIs and affects the performance of BCI system. Although, users or subjects tried to focus on the target stimulus, they still could not help being affected by conspicuous changes of the stimuli (flashes or presenting...
The brain computer interface (BCI) is an emerging technology for paralyzed people to communicate with external environments through their minds. However, current EEG equipment utilizes metal electrodes, such as gold cup, AgCl, etc., with electrolytes to attach on human skin. These wet-type electrodes are not convenient for use. It usually requires a lousy preparation process and the refill of electrolyte...
It is impossible for severely disabled people to browse or learn through the Internet due to the mere lack of independent control of the mouse. This paper proposes a brain computer interface (BCI) to aid severely disabled individuals, such as people disabled by amyotrophic lateral sclerosis (ALS), in browsing or learning on the Internet. By analyzing specific components of event-related potentials...
This paper presents a BCI (brain-computer interface) system called, "fast Phonics-to-Chinese-Character system", for individuals to write Chinese Characters using his or her brain waves. This research proposes a novel timing coding method to collocate the order of stimuli presentation. Previously, we had developed a Phonics-to-Chinese-Character system that used both the components of the...
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