73 research outputs found
Toward domotic appliances control through a self-paced P300-based BCI
During recent years there has been a growing interest in Brain Computer Interface (BCI) systems as an alternative means of interaction with the external world for people with severe motor disabilities. The use of the P300 event-related potentials as control feature allows users to choose between various options (letters or icons) requiring a very short calibration phase. The aim of this work is to improve performances and flexibility of P300 based BCIs. An efficient BCI system should be able to understand user's intentions from the ongoing EEG, abstaining from doing a selection when the user is engaged in a different activity, and changing its speed of selection depending on current user's attention level. Our self-paced system addresses all these issues representing an important step beyond the classical synchronous P300 BCI that forces the user in a continuous control task. Experimentation has been performed on 10 healthy volunteers acting on a BCI-controlled domestic environment in order to demonstrate the potential usability of BCI systems in everyday life. Results show that the self-paced BCI increases information transfer rate with respect to the synchronous one, being very robust, at the same time, in avoiding false negatives when the user is not engaged in a control task
Modern Electrophysiological Methods for Brain-Computer Interfaces
Modern electrophysiological studies in animals show that the spectrum of neural
oscillations encoding relevant information is broader than
previously thought and that many diverse areas are engaged for very simple tasks. However, EEG-based brain-computer interfaces
(BCI) still employ as control modality relatively
slow brain rhythms or features derived from preselected
frequencies and scalp locations. Here, we describe the
strategy and the algorithms we have developed for the analysis of
electrophysiological data and demonstrate their capacity to
lead to faster accurate decisions based on linear classifiers.
To illustrate this strategy, we analyzed two typical BCI tasks. (1) Mu-rhythm control of a cursor movement by a paraplegic patient. For this data, we show that although the patient received extensive training in mu-rhythm control, valuable information about movement imagination is present on the untrained high-frequency rhythms. This is the first demonstration of the importance of high-frequency rhythms in imagined limb movements. (2) Self-paced finger tapping task in three healthy subjects including the data set used in the BCI-2003 competition. We show that by selecting electrodes and frequency ranges based on their discriminative power, the classification rates can be systematically improved with respect to results published thus far
Asynchronous P300-Based Brain-Computer Interface to Control a Virtual Environment:Initial Tests on End Users
The Track of Brain Activity during the Observation of TV Commercials with the High-Resolution EEG Technology
We estimate cortical activity in normal subjects during the observation of TV commercials inserted within a movie by using high-resolution EEG techniques. The brain activity was evaluated in both time and frequency domains by solving the associate inverse problem of EEG with the use of realistic head models. In particular, we recover statistically significant information about cortical areas engaged by particular scenes inserted within the TV commercial proposed with respect to the brain activity estimated while watching a documentary. Results obtained in the population investigated suggest that the statistically significant brain activity during the observation of the TV commercial was mainly concentrated in frontoparietal cortical areas, roughly coincident with the Brodmann areas 8, 9, and 7, in the analyzed population
On the Use of EEG or MEG Brain Imaging Tools in Neuromarketing Research
Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI) methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies. By presenting data gathered through MEG and high resolution EEG we will show which kind of information it is possible to gather with these methodologies while the persons are watching marketing relevant stimuli. Such information will be related to the memorization and pleasantness related to such stimuli. We noted that temporal and frequency patterns of brain signals are able to provide possible descriptors conveying information about the cognitive and emotional processes in subjects observing commercial advertisements. These information could be unobtainable through common tools used in standard marketing research. We also show an example of how an EEG methodology could be used to analyze cultural differences between fruition of video commercials of carbonated beverages in Western and Eastern countries
Vibrotactile Feedback for Brain-Computer Interface Operation
To be correctly mastered, brain-computer interfaces (BCIs) need an uninterrupted flow
of feedback to the user. This feedback is usually delivered through the visual channel.
Our aim was to explore the benefits of vibrotactile feedback during users' training
and control of EEG-based BCI applications. A protocol for delivering vibrotactile feedback,
including specific hardware and software arrangements, was specified. In three studies
with 33 subjects (including 3 with spinal cord injury), we compared vibrotactile and visual
feedback, addressing: (I) the feasibility of subjects' training to master their EEG rhythms
using tactile feedback; (II) the compatibility of this form of feedback in presence of a visual
distracter; (III) the performance in presence of a complex visual task on the same (visual)
or different (tactile) sensory channel. The stimulation protocol we developed supports a general
usage of the tactors; preliminary experimentations. All studies indicated that the vibrotactile channel
can function as a valuable feedback modality with reliability comparable to the classical visual
feedback. Advantages of using a vibrotactile feedback emerged when the visual channel was
highly loaded by a complex task. In all experiments, vibrotactile feedback felt, after some training,
more natural for both controls and SCI users
Asynchronous P300-Based Brain-Computer Interface to Control a Virtual Environment:Initial Tests on End Users
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