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Brain Computer Interfaces (BCIs) have gained popularity in recent years and as they spread further towards becoming ubiquitous, privacy issues deserve immediate attention. In this work, we discuss BCIs' unique privacy issues and take first step toward addressing those issues by proposing a mechanism that applies multiple layers of privacy protection such as encryption, access control, code analysis,...
Brain-computer interfaces (BCIs) aim to provide a non-muscular channel to communicate with the external world through the use of the brain Electroencephalograph (EEG) activity. A crucial step in such an operation is brain signal processing methods. BCI systems use EEG as it is practical, noninvasive, cheap and has real time capability imaging technology. BCI's efficiency is dependent on brain signal...
The alpha activity of brain has a frequency range of 8-12 Hz. In order to extract the alpha activity from EEG data we propose a new procedure based on independent component analysis (ICA), which can incorporate the a prior frequency information into the ICA to extract independent components in the desired frequency range. We named this procedure as augmented ICA (Au-ICA). The performance of the proposed...
Mismatch negativity (MMN) was used to investigate the processing of different synthesized music sounds duration in the human auditory perception. Compared to the short sound, the long sound elicited a more prominent MMN occurring later than that of the short one. sLORETA computation of the mismatch responses yielded clear left-hemispheric laterality in both types of sound duration. However, the short...
Near-infrared spectroscopy (NIRS) is a non-invasive technology for measuring brain activity. Recently, the number of research papers on brain machine interface (BMI) based on NIRS technology is increasing. NIRS is a safe and convenient technique but its measurement results are unstable. To improve reliability of NIRS-based BMI, methods to extract stable data from NIRS signals are necessary. This paper...
Brain-machine interfaces (BMIs) are expected to be used to assist seriously disabled persons' communications and reintegrate their motor functions. One of the difficult problems to realize practical BMI is how to record neural activity clearly and safely. Conventional invasive methods require electrodes inside the dura mater, and noninvasive methods do not involve surgery but have poor signal quality...
Cross-modality is the development of cross link between the modalities in the brain following sensory deprivation in the early stage. Cross modality analysis was previously done with fMRI, MEG and PET images for studying the changes in cerebral activities. Instead of these imaging techniques, this work involves in deriving self similarity parameter using detrended fluctuation analysis of EEG from...
Affective Brain-Computer Interfaces (BCI) are systems that measure signals from the peripheral and central nervous system, extract features related to affective states of the user, and use these features to adapt human-computer interaction (HCI). Affective BCIs provide new perspectives on the applicability of BCIs. Affective BCIs may serve as assessment tools and adaptive systems for HCI for the general...
Research in brain-computer interface (BCI) has significantly increased during the last few years. In addition to their initial role as assisting devices for the physically challenged, BCIs are now proposed for a wider range of applications. As in any HCI application, BCIs can also benefit from adapting their operation to the emotional state of the user. BCIs have the advantage of having access to...
To investigate the neural efficiency theory of intelligence, electroencephalograms (EEG) were recorded while 15 intellectually gifted children and 15 average children performed a 2-back working memory task. The amplitude of P2, N2, and LPC were analyzed. The results showed that intellectually gifted children performed more accurately and had larger LPC mean amplitudes than their intellectually average...
On aging there is a decrease in the cognitive functions of the brain which can result in behavioral anomalies such as wandering and susceptibility to fall, typical of patients with Alzheimer's disease. In order to learn how to manage patients with cognitive impairment it is necessary to non-intrusively monitor brain activity in conjunction with body movements. To facilitate the translation of insights...
The purpose of this study was to examine the effects of conceptual similarity between target and nontarget stimuli on P300 component during a multistimulus oddball paradigm. P300 is an endogenous component of event related potentials, which can reflect the information processing of brain. It is elicited in two-stimulus oddball task in this report. The stimuli were pictures of three objects and their...
Stroke is one of the most disabling diseases that mankind has experienced. The disability caused after stroke can be effectively reduced when the patient is encouraged to undergo regular rehabilitation therapy.
This paper reports our preliminary result of microstate analysis for the spatiotemporal characteristics of Chan-meditation brain wave (electroencephalograph, EEG) based on time-varying dipolar-vector model of the alpha-map. Microstate behavior reveals subtle transience of focalized event. Multi-channel alpha-event epochs were identified by Wavelet decomposition and feature extraction. Global field...
This paper addresses the automated false positives-free detection of epileptic events by the fusion of information extracted from simultaneously recorded electroencephalographic- and electrocardiographic time-series. The approach relies on the biomedical prior knowledge for the coupling of the brain- and heart systems through the central autonomic network during temporal lobe epileptic events: neurovegetative...
Localization of the seizure focus in the brain is a challenging problem in the field of epilepsy. The complexity of the seizure-related EEG waveform, its non-stationarity and degradation with distance due to the dispersive nature of the brain as a propagation medium, make localization difficult. Yet, precise estimation of the focus is critical, particularly when surgical resection is the only therapeutic...
In this paper, a brain/computer interface is proposed. The aim of this work is the recognition of the will of a human being, without the need of detecting the movement of any muscle. Disabled people could take, of course, most important advantages from this kind of sensor system, but it could also be useful in many other situations where arms and legs could not be used or a brain-computer interface...
Recent studies have focused on the phenomena of abnormal electrical brain activity which may transition into a debilitating seizure state through the entrainment of large populations of neurons. Starting from the initial epileptogenisis of a small population of abnormally firing neurons, to the mobilization of mesoscopic neuron populations behaving in a synchronous manner, a prediction methodology...
The aim of this study is to investigate the difference of EEG dynamics on navigation performance. A tunnel task was designed to classify subjects into allocentric or egocentric spatial representation users. Despite of the differences of mental spatial representation, behavioral performance in general were compatible between the two strategies subjects in the tunnel task. Task-related EEG dynamics...
A brain-computer interface (BCI) provides the possibility to translate brain neural activity patterns into control commands without user's movement. The brain activity is most commonly measured non-invasively via standard electroencephalography (EEG), i.e., with electrodes placed on the surface of the scalp. In this article, we evaluate a BCI system based on steady-state visual evoked potentials (SSVEPs)...
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