Overcoming Inter-Subject Variability in BCI Using EEG-Based Identification

The high dependency of the Brain Computer Interface (BCI) system performance on the BCI user is a well-known issue of many BCI devices. This contribution presents a new way to overcome this problem using a synergy between a BCI device and an EEG-based biometric algorithm. Using the biometric algorithm, the BCI device automatically identifies its current user and adapts parameters of the classification process and of the BCI protocol to maximize the BCI performance. In addition to this we present an algorithm for EEG-based identification designed to be resistant to variations in EEG recordings between sessions, which is also demonstrated by an experiment with an EEG database containing two sessions recorded one year apart. Further, our algorithm is designed to be compatible with our movement-related BCI device and the evaluation of the algorithm performance took place under conditions of a standard BCI experiment. Estimation of the mu rhythm fundamental frequency using the Frequency Zooming AR modeling is used for EEG feature extraction followed by a classifier based on the regularized Mahalanobis distance. An average subject identification score of 96 % is achieved

High-Resolution Movement EEG Classification

The aim of the contribution is to analyze possibilities of high-resolution movement classification using human EEG. For this purpose, a database of the EEG recorded during right-thumb and little-finger fast flexion movements of the experimental subjects was created. The statistical analysis of the EEG was done on the subject's basis instead of the commonly used grand averaging. Statistically significant differences between the EEG accompanying movements of both fingers were found, extending the results of other so far published works. The classifier based on hidden Markov models was able to distinguish between movement and resting states (classification score of 94–100%), but it was unable to recognize the type of the movement. This is caused by the large fraction of other (nonmovement related) EEG activities in the recorded signals. A classification method based on advanced EEG signal denoising is being currently developed to overcome this problem

The Law and Regulation of Payment Services

Právní regulace platebních služeb Abstrakt Práce se věnuje tématu platebních služeb, a to zejména v souvislosti s nabytím účinnosti druhé směrnice o platebních službách. Cílem práce je vyhodnotit, které činnosti na finančním trhu podléhají regulaci platebních služeb, identifikovat osoby oprávněné platební služby poskytovat a analyzovat některá práva a povinnosti vznikající mezi uživateli a poskytovateli platebních služeb. Autor se snaží také o analýzu změn, které druhá směrnice o platebních službách do českého práva přinesla, a zamýšlí se nad tím, do jaké míry tento předpis může ovlivnit trh platebních služeb a subjekty na něm působící. Práce je členěna do pěti kapitol, přičemž první kapitola se věnuje jednotlivým platebním službám a druhá vymezuje činnosti, které platebními službami nejsou. Další kapitola obsahuje přehled tuzemských i evropských předpisů, které se na platební služby a činnost jejich poskytovatelů vztahují. Čtvrtá kapitola je věnována osobám, které jsou oprávněny platební služby poskytovat, a práci uzavírá pátá kapitola popisující právní vztahy vznikající při poskytování platebních služeb, zejména závazky ze smluv o platebních službách, informační povinnosti poskytovatelů platebních služeb a odpovědnost za neautorizované a nesprávně provedené platební transakce. Autor dochází k závěru, že...The Law and Regulation of Payment Services Abstract The thesis deals with the subject of payment services, especially in the context of the Payment Services Directive 2, which recently came into force. The aim of the thesis is to evaluate which activities on the financial market are subject to regulation of payment services, to identify the persons authorised to provide payment services and to analyse certain rights and obligations arising between payment service users and payment service providers. The author also tries to analyse the changes brought by the Payment Services Directive 2 into the Czech law and considers the possible impact of such legislation on the payment services market and on the persons operating on it. The thesis is divided into five chapters, the first chapter deals with individual payment services; the second chapter defines activities that are out of the scope of payment services. The next chapter contains an overview of both Czech and EU law applicable to payment services, payment service providers and their activities. The fourth chapter is dedicated to the persons authorized to provide payment services and the fifth chapter describes the legal relationships arising when providing payment services, focusing mainly on the payment service contract, information duty of payment...Department of Financial Law and FinancesKatedra finančního práva a finanční vědyFaculty of LawPrávnická fakult

EEG Signal Classification: Introduction to the Problem

The contribution describes the design, optimization and verification of the off-line single-trial movement classification system. Four types of movements are used for the classification: the right index finger extension vs. flexion as well as the right shoulder (proximal) vs. right index finger (distal) movement. The classification system utilizes hidden information stored in the characteristic shapes of human brain activity (EEG signal). The great variability of EEG potentials requires using of context information and hence the classifier based on Hidden Markov Models (HMM). The suitable parameterization, model structure as well as training and classification process are suggested on the base of spectral analysis results and experience with the speech recognition. The training and the classification are performed with the disjoint sets of EEG realizations. Classification experiments are performed with 10 randomly chosen sets of EEG realizations. The final average score of the distal/proximal movement classification is 80%; the standard deviation of classification results is 9%. The classification of the extension / flexion gives comparable results

ICA Model Order Estimation Using Clustering Method

In this paper a novel approach for independent component analysis (ICA) model order estimation of movement electroencephalogram (EEG) signals is described. The application is targeted to the brain-computer interface (BCI) EEG preprocessing. The previous work has shown that it is possible to decompose EEG into movement-related and non-movement-related independent components (ICs). The selection of only movement related ICs might lead to BCI EEG classification score increasing. The real number of the independent sources in the brain is an important parameter of the preprocessing step. Previously, we used principal component analysis (PCA) for estimation of the number of the independent sources. However, PCA estimates only the number of uncorrelated and not independent components ignoring the higher-order signal statistics. In this work, we use another approach - selection of highly correlated ICs from several ICA runs. The ICA model order estimation is done at significance level α = 0.05 and the model order is less or more dependent on ICA algorithm and its parameters

Recovery of Cerium Dioxide from Spent Glass-Polishing Slurry and Its Utilization as a Reactive Sorbent for Fast Degradation of Toxic Organophosphates

The recovery of cerium (and possibly other rare earth elements) from the spent glass-polishing slurries is rather difficult because of a high resistance of polishing-grade cerium oxide toward common digestion agents. It was shown that cerium may be extracted from the spent polishing slurries by leaching with strong mineral acids in the presence of reducing agents; the solution may be used directly for the preparation of a ceria-based reactive sorbent. A mixture of concentrated nitric acid and hydrogen peroxide was effective in the digestion of partially dewatered glass-polishing slurry. After the removal of undissolved particles, cerous carbonate was precipitated by gaseous NH3 and CO2. Cerium oxide was prepared by a thermal decomposition of the carbonate precursor in an open crucible and tested as reactive sorbent for the degradation of highly toxic organophosphate compounds. The samples annealed at the optimal temperature of approximately 400°C exhibited a good degradation efficiency toward the organophosphate pesticide fenchlorphos and the nerve agents soman and VX. The extraction/precipitation procedure recovers approximately 70% of cerium oxide from the spent polishing slurry. The presence of minor amounts of lanthanum does not disturb the degradation efficiency

The Mini Labyrinth - a Simple Benchmark for Radiation Protection and Shielding Analysis

The Mini Labyrinth experiment is a simple neutron and gamma shielding experiment developed at STU, inspired by the ALARM-CF-AIR-LAB-001 ICSBEP benchmark experiment. The STU Mini Labyrinth is approximately ten times smaller and consists of NEUTRONSTOP shielding blocks. This paper describes the second version of the Mini Labyrinth experiment and presents the results of the neutron and gamma fields simulation and measurement. The PuBe neutron source with the emission rate of 1.0E7 n/s was utilized in the experiment. The measurement of gamma ambient dose equivalent H*(10) and neutron count rates is performed by the Thermo Scientific RadEye portable survey meter. The simulation part was carried out using the state-of-the-art MCNP6 and SCALE6 MONACO stochastic calculation tools taking into account the detailed geometry of the labyrinth and combined neutron and gamma source of particles. The comparisons were performed between codes and experiment, based on the dose rate in the unique detection positions and using a 2D map of neutron and photon fluxes. The propagation of cross-section uncertainties was investigated through shielding analysis. Partial agreement between codes and measurement was achieved, however serious discrepancies near the PuBe source were identified