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Motor imagery (MI) based on brain computer interfaces (BCIs) have been widely applied for upper limb motor rehabilitation. Due to the fact that a large number of disabled people need to restore or improve walking ability, it is also important to investigate the use of MI-based BCIs for lower limb motor rehabilitation. The brain activity of lower limb MI is more difficult to detect because of low reliability...
In this preliminary study, we explore the brain activity of healthy subjects during visual sustained attention task using a low-cost electroencephalography headset. The main objective is to study the ability of subjects to detect and respond to stimulus changes which occur infrequently during the time using Emotiv EPOC system. 14-Channels EEG data were recorded while subjects participated in 10 minutes...
This paper presents a novel method of image classification for trend prediction based on integration of visual and fNIRS features. It is expected that classification of images in the same object category in terms of generation enables trend prediction. However, since images in the same object category have similar visual features, a limit of accuracy exists for image classification by using only visual...
This study is to examine the possibility of a brain-scientific approach of the fashion-store visual merchandising display (VMD). In marketing area, VMD has become a research topic of interest. However, a few VMD research has been done by using human brain signals. In this work, the hemodynamic responses (HRs) in the prefrontal cortex (PFC) using functional near-infrared spectroscopy were measured...
The purpose of this study was to investigate the effect of spatial ability task to the cognitive performance and EEG activity. Nine participants were participated in this study. Participants were instructed to practice the spatial ability task. While performing the spatial ability task, EEG activity were recorded by using the lightweight EEG device, Mindwave Mobile, NeuroSky, Inc. The results revealed...
Objective: The purpose of this study was to determine the effect of Jenga game brain training for cognitive performance and EEG activity in Thai healthy older adults. Material and Methods: Six participants were participated. Participants were instructed to practice Jenga gam brain training. During practice memory and attention games, EEG activity were recorded by using the lightweight EEG device,...
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...
Working memory (WM) plays a critical role in cognitive skills such as, learning, reasoning, and language comprehension. WM capacity is widely used as a predictor of academic performance and many other cognitive skills. Yet, how the human brain coordinates this complex skill through its functional networks and also whether individual's WM limitations are due to contrasts in regional activation or cross-regional...
White matter segmentation is an essential step to study whole-brain structural connectivity via diffusion MRI white matter tractography. One important goal of segmentation methods is to improve consistency of the white matter segmentations across multiple subjects. In this study, we quantitatively compare two popular white matter segmentation strategies, i.e., a cortical-parcellation-based method...
Resting-state fMRI provides challenging data that needs to be analyzed without knowledge about timing or duration of neuronal events. The “total activation” framework is one recent approach that combines temporal and spatial regularization to deconvolve the fMRI signals; i.e., undo them from the influence of the hemodynamic response. The temporal regularization is using generalized total variation...
Driver's mental work load has been known for one of the significant causes of traffic accidents in driving situations. Hence, in this study, we investigate the effects of mental work load on brain activity during an emergency situation in driving simulator. We compare the differences of electroencephalography (EEG) signals between emergency situations without- and with mental work load on simulated...
Functional Magnetic Resonance Imaging (fMRI) has been valuable to the current understanding of brain function and pre-operative evaluation of patients. In the recent years, the technique has been increasingly applied to the cases when the subject is at rest, also referred to as the resting-state fMRI. Resting-state fMRI measures spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal...
Brain decoding (i.e., retrieving information from brain signals by employing machine learning algorithms) has recently received considerable attention across many communities. In a typical brain decoding paradigm, different types of stimuli are shown to the participant of the neuroimaging experiment, while his/her concurrent brain activity is captured using neuroimaging techniques. Then a machine...
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...
By applying a basic knowledge of brain-computer interfaces and brain stimulation, we introduce a novel architecture for brain-to-brain communication (B2B). Two main issues presented herein are brain synchronization and message modulation. According to our proposed B2B architecture, we assume that the higher the root mean square (RMS) of the voltage across two brains, the easier it is to recognize...
Glaucoma is the second leading cause of blindness and it has been the topic of massive studies to explore the underlying mechanisms of the disease. Resting-state neuroimaging studies have been widely applied to investigate the functional damage of the brain, but little is known about the alterations of the interhemispheric resting-state functional connectivity (RSFC) in patients with primary open-angle...
Episodic memory dysfunction is one of the hallmark symptoms of Alzheimer's disease (AD) and mild cognitive impairment (MCI). This cognitive impairment may be related to abnormal brain structure and activity. Functional connectivity mapping (FCM) analysis provides a powerful tool for exploring the topology of human brain function using magnetic resonance imaging (MRI). Thus, it would be advantageous...
A measurement method for the evaluation of the image complexity based on SIFT&K-means algorithm, namely the estimation of the mismatch between the target and the interesting points has been introduced in our previous research. Based on this method, we have made some improvements to calculate the image complexity of images with different memory targets. The improved algorithm SIFT&AIM&K-means...
Blinking has two functions: to moisturize eyes and as a defensive response to the environment and responses caused by the by mental processes. In this paper, we investigate statistical characteristics of blinks and blink rate variability of 11 subjects. The subjects are presented with a reading/memorization session preceded and followed by resting sessions. EEG signals were recorded during these sessions...
The body schema is a brain function to grasp own body location spatially. When a person uses tools or manipulates machines, the body schema is modified unconsciously, and he/she perceives these tools or machines as a part of his/her own body. In this study, brain activation adapting the strength of the body schema modification was investigated, and the possibility to interfere the body schema by electrical...
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