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Eye blink (EB) artifacts generated during eye blinks often contaminate electroencephalogram (EEG) signal. Previously Empirical Mode Decomposition (EMD) and Canonical Correlation Analysis (CCA), hybrid EMD-CCA were developed for EB artifact removal in EEG. However, EMD restricts the hybrid algorithm for real time implementation due to its slow processing nature, hence the algorithm has to be enhanced...
Tang poetry, as one of the most typical ways for ancient Chinese to express their emotions, has been continuously inherited for millenniums in China. Nowadays, though our way of life has changed dramatically, the traditional culture about Tang poetry is still affecting us deeply. However, the psychological effect of Tang poetry remains unclear currently. Motivated by this, we aim to investigate the...
Adaptive learning is a promising approach to education, in which instructional methods and materials are selected according to the performance of students. In this manner, the learning process can be tailored to the needs and strengths of students in order to maximize efficiency. Advances in internet technology and portable devices has led to the development of e-learning platforms outside the traditional...
This study aimed to compare two off-the-shelf sleep tracking devices, Fitbit (wearable fitness wristband) and Neuroon (wearable EEG eye mask), for measuring sleep under free living conditions. Taking the measurements of a clinical sleep monitor as the ground truth, we compared the measurements of Fitbit and Neuroon on total sleep time (TST), wake after sleep onset (WASO), the number of awakenings...
A Brain-Computer Interface (BCI) speller system based on the Steady-State Visually Evoked Potentials (SSVEP) paradigm is presented. The potentials are elicited through the gaze fixation at one out of the four checkerboards shown on screen, which are flickering at 5, 12, 15 and 20 Hz. After the feature extraction, two dimensionality reduction algorithms, Principal Components Analysis (PCA) and Linear...
Most brain disorders including Alzheimer's disease (AD) are related to alterations in the normal brain network organization and function. Exploring these network alterations using non-invasive and easy to use technique is a topic of great interest. In this paper, we collected EEG resting-state data from AD patients and healthy control subjects. Functional connectivity between scalp EEG signals was...
Long monitoring tasks without regular actions, are becoming increasingly common from aircraft pilots to train conductors as these systems grow more automated. These task contexts are challenging for the human operator because they require inputs at irregular and highly interspaced moments even though these actions are often critical. It has been shown that such conditions lead to divided and distracted...
Among the many cell types involved in epileptogenesis, the GABAergic interneurons are of great interests, largely due to their context-dependent role in controlling cellular excitability and dynamic behavior in seizure. By controlling GABAergic interneuron activity with optogenetic technology, we sought to block seizure activity in the hippocampus in a 4-aminopyridine induced seizure model in mice...
Biometrie recognition of persons are widely explored nowadays to develop robust and trustworthy security systems. On account of the unique neural signature of each person, the brain activity recorded by Electroencephalogram (EEG) has recently been identified as a potential biometric trait. In this paper, we propose an online EEG-based biometric system which utilizes the activations of brain towards...
Electrooculography (EOG) artifacts, generated by winking or other eye's movements, should be eliminated because they are the cause of the wrong decision in analysis the Electroencephalography (EEG) data, especially in the diagnosis of epilepsy. One of the efficient methods for signal separation is the Second order blind identification (SOBI), a blind source separation technique. In most cases, the...
The performance of classification of various mental states using Electroencephalography (EEG) is often limited by the lack of information regarding the most discriminative channels and frequency bands. The paper proposes a Canonical Correlation Analysis (CCA) of EEG recorded during bilateral imagined hand movement. CCA determines linear transformation of EEG that is maximally correlated with a transformed...
Emotional recognition as the key technology in the field of emotion computing has received more and more attentions in applications such as human-computer interaction, medical-assisted diagnosis and multimedia intelligence recommendation, and it has important research and application value. EEG recognition based on EEG is a commonly used and effective method of emotion recognition. More and more scholars...
Ocular artefacts caused by eye movements can distort Electroencephalogram (EEG) recordings. It is important to obtain clean EEG signals in diagnosing and interpreting diseases. Meaningful EEG signals should not be distorted during the removal of artefacts. In this study, Independent Component Analysis and Artificial Neural Network were used together to remove ocular artefacts. The method was tested...
Highly interactive educational contents using games are widely used, and objective evaluation of these real-time is required. In order to do this, we recorded brain waves under several interactive tasks and game situations in subjects and tried to analyze them. As a result, we focused on the proportion of beta wave components, which suggested the possibility of being able to distinguish between simple...
Neurofeedback training is one type of the biofeedback training that allows the subject do self-regulation during the training according to his/her real-time brain activities recognized from Electroencephalogram (EEG) and given to him/her through visual, audio or haptic feedback. The Neurofeedback training has been proved to be helpful in improvement of cognitive abilities not only for patients with...
The electroencephalography (EEG) data records vast amounts of human cerebral activity yet is still reviewed primarily by human readers. Most of the times, the data is contaminated with non-cerebral originated signals, called artifacts, which could be very difficult to visually detect and, undiscovered, could damage the neural information analysis. The purpose of our work is to detect the artifacts...
A novel method for removing eye-blink artifacts from brain EEG recordings is presented. It is proposed to use multichannel Wiener filter (MWF) indirectly. Namely, the eye-blink signal estimate is obtained first. For this purpose only a small subset of the frontal electrodes is used (so that extra EOG sensors are unnecessary). Then, the eye-blink estimate is subtracted from the noisy EEG signal in...
To better characterize movement-related neurophysiological change, the authors propose to measure not only neural activity through the electroencephalogram (EEG) but also cerebral blood flow (CBF) using a new technology, near-infrared diffuse correlation spectroscopy (DCS). A preliminary trial is described, in which EEG, DCS, and exerted force were simultaneously recorded during a cue-triggered hand...
Fast and accurate measuring depth of anesthesia (DoA) during heavy surgeries (e.g. orthopedic or neurosurgery) is still a challenge. Late estimation of DoA in critical conditions may lead to severe effects such as a comma or conscious state, and jeopardize patient's life accordingly. Recently, several attempts have been made to elicit an accurate DoA index by analyzing electroencephalogram (EEG) signals,...
This paper designs and implements a Steady State Visually Evoked Potential (SSVEP) intelligent home service system based on Canonical Correlation Analysis (CCA), which realizes that electroencephalogram (EEG) controls home service. The system includes a stimulus module, a data acquisition module, a data analysis module and a controlled module. Experiments show that the correct accepting rate of instructions...
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