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This study aimed to evaluate the modifications of electroencephalographic (EEG) power spectra in overweight and obese patients. EEG was recorded while performing the Stroop Color Word Test. Stroop Color Word Test was performed and EEG activity was also monitored during the experiment. Paired t-test and independent t-test were used to show statistical difference between baseline and Stroop Color Word...
This work deals to present some problems related to the analysis of the brain activity of a user when he detects an error in the classification or the interpretation of his previous intention. This error can be detected after each correct or incorrect classification of a brain activity. Our study is based on the visual stimulation using SSVEP. Electrodes have to be installed on the scalp of the user...
Imagine you are facing a mirror, seeing at the same time both your real body and a virtual display of your brain in activity and perfectly superimposed to your real image “inside your real skull”. In this paper, we introduce a novel augmented reality paradigm called “Mind-Mirror” which enables the experience of seeing “through your own head”, visualizing your brain “in action and in situ”. Our approach...
Decoding perceptual or cognitive states based on brain activity measured using functional Magnetic Resonance Imaging (fMRI) can be achieved using machine learning algorithms to train classifiers of specific stimuli. However, the high dimensionality and intrinsically low Signal-to-Noise Ratio (SNR) of fMRI data poses great challenges to such techniques. The problem is aggravated in the case of multiple...
Brain-computer interface (BCI) systems allow people to send messages or commands without moving, and hence can provide an alternative communication and control channel for people with limited motor function. In this study, we demonstrate a BCI system for orthosis control. Our BCI was asynchronous, meaning that subjects could move the orthosis whenever they wanted, instead of pacing themselves to external...
One of the foremost goals of rehabilitative Brain-Computer Interface (BCI) research is to design a mental typewriter, that enables paralyzed patients to communicate with their environment based on their brain activity. For the most popular candidate, the so called Matrix Speller, a recent study has shown that the spelling accuracy completely breaks down when the user is not allowed to fixate the target...
Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is increasingly used to monitor the brain activity. The interactions between the scanner magnetic field, the patient's body, and the EEG electrodes generate a pulsation artifact called ballistocardiogram (BCG) which is synchronized with the patient's heart beat. The BCG artifact is considered here...
Brain-computer interfaces (BCIs) open a new valuable communication channel for people with severe neurological or motor degenerative diseases, such as ALS patients. On the other hand, the ability to teleoperate robots in a remote scenario provides a physical entity embodied in a real environment ready to perceive, explore, and interact. The combination of both functionalities provides a system with...
Chunking is a unifying information-processing mechanism in human cognition and plays an important role in problem solving. In the present experiment, we use a Chinese character chunking task to explore the neural basis of the goal-oriented chunking, which were classified into loose chunking and tight chunking. The behavioral result confirmed our prediction that the tight chunking was more difficult...
Video game playing is an attractive form of entertainment among school-age children. Although this activity has many adverse effects on child development, there have been only a few studies examining the biological effects of video games on brain activity. The aims of this study were i) to investigate effects of video game playing on attentional capacity and visual skills ii) to relate training induced...
Artificial emotion study will be of utmost importance in future artificial intelligence research. In this paper, an emotion understanding system based on brain activity and ldquoGISTrdquo is newly proposed to categorize emotions reflected by natural scenes. According to the strong relationship of human emotion and the brain activity, functional magnetic resonance imaging (fMRI) and electroencephalography...
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