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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...
The sensorimotor modulation is degenerated due to aging, and it may cause the elderly falling in a daily activity. The clinical balance assessments, somatosensory test, muscle strength and the joint motion measurement are usually applied to evaluate the falling potential in the aged population. Nevertheless, the ceiling effect is found among the sub-healthy elderly who has a highly functional mobility...
Gaze-based virtual keyboards provide an effective interface for text entry by eye movements. The efficiency and usability of these keyboards have traditionally been evaluated with conventional text entry performance measures such as words per minute, keystrokes per character, backspace usage, etc. However, in comparison to the traditional text entry approaches, gaze-based typing involves natural eye...
Brain-computer interface (BCI) is a modern useful tool of bypassing usual channels of muscle and peripheral nervous system to establish a direct connection between brain and external devices and to restore fundamental communication and control skills. Steady-state visual evoked potential (SSVEP), as one of the most popular EEG modality, has been widely used in BCI applications. For SSVEP BCI, the...
This research aims to study the neural influence of conflict between brand and product performance on consumer decision. In the experiment, stimuli of products with brand and performance information were displayed randomly. 22 subjects need to decide whether to buy, while the event-related potentials (ERPs) were recorded. The stimuli were divided into four conditions based on the consistency of brand...
Target image detection based on rapid serial visual presentation (RSVP) paradigm is a typical brain-computer interface with various applications, such as image retrieval. In an RSVP paradigm, the P300 component is detected to determine the target image, which requires high-precision single-trial P300 detection methods. However, compared to multi-trial P300 detection methods, the performance of single-trial...
Dual tasking refers to the simultaneous execution of two tasks with different demands. In this study, we aimed to investigate the effect of a second task on a main task of motor execution and on the ability to detect the cortical potential related to the main task from non-invasive electroencephalographic (EEG). Participants were asked to perform a series of cue-based ankle dorsiflexions as the primary...
Sparse Bayesian Learning (SBL) is a widely used framework which helps us to deal with two basic problems of machine learning, to avoid overfitting of the model and to incorporate prior knowledge into it. In this work, multiple linear regression models under the SBL framework are used for the problem of multiclass classification when multiple subjects are available. As a case study, we apply our method...
Brain-machine interface (BMI) can be used to control robotic arm to assist paralysis people improving their quality of life. However process control of objects grasping is still a complex task for BMI users. High efficiency and accuracy is hard to achieve in objects grasping process even after extensive training. An important reason is lack of sufficient feedback information for performing the closed-loop...
Visual fixation is an item of the Coma Recovery Scale-Revised (CRS-R), it is difficult to be detected by clinicians using the behavioral scales because of fluctuations of arousal level and the presence of motor impairment in disorders of consciousness (DOC) patients. Brain-computer interfaces (BCIs), which directly detect brain response without any behavioral expression, can be used to evaluate a...
Disabled people often have difficulties in conveying their intentions to assistive vehicles, which can transport them to desired destinations, and a P300 brain-computer interface (BCI) system may help them use intelligent assistive vehicles by selecting a desired destination from predefined ones. However, real world driving often exposes the P300 BCI system to various illumination and noise environments...
Electroencephalography (EEG) and brain-computer interfaces (BCI) are receiving increasing attention and expanding application in stroke study. To identify stroke patients and normal controls during mental rotation task, common spatial pattern (CSP) algorithm is employed to extract features from binary-class EEG which will be further to form the dictionary for sparse representation. In the classification...
Recently, SSVEP detection from EEG signals has attracted the interest of the research community, leading to a number of well-tailored methods, such as Canonical Correlation Analysis (CCA) and a number of variants. Despite their effectiveness, due to their strong dependence on the correct calculation of correlations, these methods may prove to be inadequate in front of potential deficiency in the number...
Working memory processing is central for higher-order cognitive functions. Although the ability to access and extract working memory load has been proven feasible, the temporal resolution is low and cross-task generalization is poor. In this study, EEG oscillatory activity was recorded from sixteen healthy subjects while they performed two versions of the visual n-back task. Observed effects in the...
As a new biometric, the Electroencephalogram (EEG) signal has the advantages of invisibility, non-clonability, and non-coercion compare to traditional biometrics. However, the real-time and stability are the difficulties that the current EEG-based person authentication systems face. In this paper, we design a real-time and stable person authentication system using EEG signals, which are elicited by...
Multi-target stimulus coding plays an important role in a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). In conventional SSVEP-based BCIs, a large interval between two neighboring stimulus frequencies is often used to improve classification accuracy. Although recent progresses in stimulus coding and target identification methods that have significantly improved...
Attenuation of alpha wave is considered as the most valid marker of sleep onset during sleep, but this has received little attention during driving. Interestingly, from our simulated driving experiments, a new alpha wave's attenuation-disappearance phenomenon was observed to frequently appear in eye closure events (ECEs), with an obvious split point, which divides ECE into alpha attenuation phase...
The aim of this study is to determine the potential prognostic value of using Brain-computer Interface (BCI) to identify patients with disorder of consciousness (DOC), who show potential for recovery. A retrospective study involved 51 patients with DOC were conducted. Each patient conducted in a BCI experiment to detect awareness and received a 3-months follow-up. The BCI accuracies were correlated...
The development of automatic detectors for EEG patterns is often challenged by the quality and availability of training events. We have implemented data depuration, augmentation and balancing steps in the development process of a sleep-spindle detector and measured their effect on the detection performance. The training data depuration is based on kernelized k-means clustering and allowed re-grouping...
For a practical intracranial brain computer interface (BCI), minimizing the invasiveness of the electrode implantation is crucial. In this study, we used only one intracranial electrode to implement an online BCI for fast typing. When the subject attended the virtual button containing visual motion stimuli, prominent responses were elicited at the stereo-EEG (SEEG) electrodes within the fMRI defined...
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