In this work, exfoliated graphene nanoplatelets (GNPs)/polyaniline (PANI) nanocomposites have been prepared by sequential processing comprising: (i) a first aniline oxidative polymerization step under acidic conditions and (ii) mechanical blending with GNPs at different percentages. Thermoelectric pellets of the hybrid materials obtained suitable circular geometry means cold pressing. parameters determined room temperature (electrical conductivity, Seebeck coefficient thermal conductivity)....

Techniques based on electroencephalography (EEG) measure the electric potentials scalp and process them to infer location, distribution, intensity of underlying neural activity. Accuracy in estimating these parameters is highly sensitive uncertainty conductivities head tissues. Furthermore, dissimilarities among individuals are ignored when standarized values used. In this paper, we apply maximum-likelihood maximum a posteriori (MAP) techniques simultaneously estimate layer conductivity...

Abstract We compare three global configuration search methods on a scalable model problem to measure relative performance over range of molecule sizes. Our is 2‐D polymer composed atoms connected by rigid rods in which all pairs interact via Lennard–Jones potentials. The minimum energy can be calculated analytically. are hybrids combining sampling algorithm with local refinement technique. simulated annealing ( SA ), genetic algorithms GA and random search. Each these uses conjugate gradient...

In this paper, we propose a statistical selection procedure by which various mental tasks can be characterized specific brain functional connectivity. Different connectivity patterns are identified the partial directed coherence (PDC) is frequency-domain metric that provides information about directionality in interaction between signals recorded at different sensors. The basis of our analysis connectivities revealed their repeated appearance and larger PDC magnitudes sets...

The use of transcranial direct current stimulation (tDCS) has been related to the improvement motor and learning tasks. research studies effects an asymmetric tDCS setup over brain connectivity, when subject is performing a imagery (MI) task during five consecutive days. A brain–computer interface (BCI) based on electroencephalography simulated in offline analysis study effect that different electrode configurations for BCI. This way, BCI performance used as validation index by classifier...

<title>Abstract</title> The functional brain connectivity of electroencephalography (EEG) data that was acquired during the process learning how to touch-type using Colemak keyboard distribution is analyzed in this paper. partial directed coherence (PDC) EEG alpha, beta, and gamma rhythms used assess at different stages. As result, patterns common volunteers are found as representative underlying processes. In particular, within alpha rhythm low-difficulty tasks exhibit greatest...

We present forward modeling solutions in the form of array response kernels for electroencephalography (EEG) and magnetoencephalography (MEG), assuming that a multilayer ellipsoidal geometry approximates anatomy head dipole current models source. The use an is useful cases which incorporating anisotropy important but better model cannot be defined. structure our facilitates analysis inverse problem by factoring lead field into product source kernel containing information corresponding to...

In this paper, we compare the performance of brain-computer interfaces (BCIs) when different feedback modalities are used. particular, study effects auditory or vibrotactile presented to reinforce users' (positive feedback) correct a poor achievement in controlling BCI (negative feedback). Then, possible combinations (positive/negative auditory/vibrotactile is compared against traditional visual for case users operating based on electroencephalographic (EEG) measurements motor imaginery...

Fetal magnetoencephalography (fMEG) is a non-invasive technique where measurements of the magnetic field outside maternal abdomen are used to infer source location and signals fetus' neural activity. There number aspects related fMEG modelling that must be addressed, such as conductor volume, fetal position orientation, gestation period, etc. We propose solution forward problem based on an ellipsoidal head geometry. This model has advantage highlighting special characteristics inherent...

New trends on brain-computer interface (BCI) design are aiming to combine this technology with immersive virtual reality in order provide a sense of realism its users. In study, we propose an experimental BCI control telepresence system using motor imagery (MI). The is the that users can movement NAO humanoid robot first person perspective (1PP), i.e., as if was his/her own. We analyze functional brain connectivity between 1PP and 3PP during our graph theory properties such degree,...

In this paper we propose spatial filters for a linear regression model which are based on the minimum-variance pseudo-unbiased reduced-rank estimation (MV-PURE) framework. As sample application, consider problem of reconstruction brain activity from electroencephalographic (EEG) or magnetoencephalographic (MEG) measurements. The proposed come in two versions depending whether not EEG/MEG forward explicitly considers interfering way originating regions different to those main interest, but...

We study the relationship between electroencephalographic (EEG) coherence and accuracy in operating a brain-computer interface (BCI). In our case, BCI is controlled through motor imagery. Hence, number of volunteers were trained using different training paradigms: classical visual feedback, auditory stimulation, functional electrical stimulation (FES). After each session, volunteers’ was assessed, event-related (ErCoh) calculated for all possible combinations pairs EEG sensors. at least four...

We study the performance of various beamformers for estimating a current dipole source at known location using electroencephalography (EEG) and magnetoencephalography(MEG). present our in form generalized sidelobe canceler (GSC). Under this structure, beamformer can be solved by finding filter that achieves minimum mean-squared error (MMSE) between mainbeam response filtered observed signal. express MMSE as function filter's rank use it criterion to evaluate beamformers. do not make any...

We consider the problem of dipole source signals estimation in electroencephalography (EEG) using beamforming techniques ill-conditioned settings. take advantage link between linearly constrained minimum-variance (LCMV) beamformer sensor array processing and best linear unbiased estimator (BLUE) regression modeling. show that recently introduced reduced-rank extension BLUE, named pseudo-unbiased (MV-PURE), achieves much lower error not only than LCMV beamformer, but also previously derived...

We consider the problem of electroencephalography (EEG) and magnetoencephalography (MEG) source localization using beamforming techniques. Specifically, we propose a reduced-rank extension recently derived multi-source activity index (MAI), which itself is an classical neural to case. show that, for uncorrelated dipole sources any nonzero rank constraint, proposed (RR-MAI) achieves global maximum when evaluated at true positions. Therefore, RR-MAI can be used localize multiple...

We explore the possibility of assessing acquisition a new skill through electroencephalographic (EEG) measurements. In particular, we propose an experiment to monitor process learning type using Colemak keyboard layout during twelve-lessons training. As first step, are interested in identifying statistically significant changes power spectral density (PSD) various EEG rhythms at stages process. Those taken into account only when probabilistic measure cognitive state ensures high engagement...