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Search results for: EEQ
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CLINICAL EEG AND NEUROSCIENCE
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Balance recognition on the basis of EEG measurement.
PublicationAlthough electroencephalography (EEG) is not typically used for verifying the sense of balance, it can be used for analysing cortical signals responsible for this phenomenon. Simple balance tasks can be proposed as a good indicator of whether the sense of balance is acting more or less actively. This article presents preliminary results for the potential of using EEG to balance sensing....
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Metody redukcji artefaktów w zapisie EEG.
PublicationPrzegląd i opis metod badania EEG jego uwarunkowań technicznych oraz problemy z tym związane. Dokonano przeglądu metod pozwalających na zredukowanie bądź eliminacje artefaktów w zapisie EEG.
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Decoding imagined speech for EEG-based BCI
PublicationBrain–computer interfaces (BCIs) are systems that transform the brain's electrical activity into commands to control a device. To create a BCI, it is necessary to establish the relationship between a certain stimulus, internal or external, and the brain activity it provokes. A common approach in BCIs is motor imagery, which involves imagining limb movement. Unfortunately, this approach allows few commands. As an alternative, this...
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Tensor Decomposition for Imagined Speech Discrimination in EEG
PublicationMost of the researches in Electroencephalogram(EEG)-based Brain-Computer Interfaces (BCI) are focused on the use of motor imagery. As an attempt to improve the control of these interfaces, the use of language instead of movement has been recently explored, in the form of imagined speech. This work aims for the discrimination of imagined words in electroencephalogram signals. For this purpose, the analysis of multiple variables...
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Labeler-hot Detection of EEG Epileptic Transients
PublicationPreventing early progression of epilepsy and sothe severity of seizures requires effective diagnosis. Epileptictransients indicate the ability to develop seizures but humansoverlook such brief events in an electroencephalogram (EEG)what compromises patient treatment. Traditionally, trainingof the EEG event detection algorithms has relied on groundtruth labels, obtained from the consensus...
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ESQ: A Journal of the American Renaissance
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Transfer learning in imagined speech EEG-based BCIs
PublicationThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublicationIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublicationThe aim of this paper is to present a system for automatic assigning electroencephalographic (EEG) signals to appropriate classes associated with brain activity. The EEG signals are acquired from a headset consisting of 14 electrodes placed on skull. Data gathered are first processed by the Independent Component Analysis algorithm to obtain estimates of signals generated by primary sources reflecting the activity of the brain....
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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublicationThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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Efficiency of exciton splitting in organic photovoltaic cells within EQE spectrum
PublicationThe paper presents a procedure of estimating the efficiency of exciton splitting at ED/EA interface. The procedure consists in evaluation of splitting of excitons into electron-hole pairs on the basis of the external quantum efficiency spectra of planar cells and spectra of absorbance of active organic layers. The fitting parameters are the exciton splitting probabilities at ED/EA interface. The presented procedure was applied...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Comparison of Methods for Real and Imaginary Motion Classification from EEG Signals
PublicationA method for feature extraction and results of classification of EEG signals obtained from performed and imagined motion are presented. A set of 615 features was obtained to serve for the recognition of type and laterality of motion using 8 different classifications approaches. A comparison of achieved classifiers accuracy is presented in the paper, and then conclusions and discussion are provided. Among applied algorithms the...
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Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion
PublicationA rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion....
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Brain-computer interaction based on EEG signal and gaze-tracking information = Analiza interackji mózg-komputer wykorzystująca sygnał EEg i informacje z systemu śledzenia punktu fiksacji wzroku
PublicationThe article presents an attempt to integrate EEG signal analysis with information about human visual activities, i.e. gaze fixation point. The results from gaze-tracking-based measurement were combined with the standard EEG analysis. A search for correlation between the brain activity and the region of the screen observed by the user was performed. The preliminary stage of the study consists in electrooculography (EOG) signal processing....
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EE-EVALUATION ENGINEERING
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Implementation of the Indoor Environmental Quality (IEQ) Model for the Assessment of a Retrofitted Historical Masonry Building
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Monitoring of herpesvirus anguillae (AngHV-1) infections in the European eel in north-west Poland
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Rating by detection: an artifact detection protocol for rating EEG quality with average event duration
PublicationQuantitative evaluation protocols are critical for the development of algorithms that remove artifacts from real EEG optimally. However, visually inspecting the real EEG to select the top-performing artifact removal pipeline is infeasible while hand-crafted EEG data allow assessing artifact removal configurations only in a simulated environment. This study proposes a novel, principled approach for quantitatively evaluating algorithmically...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Equilibrium constants (Keq) of reforming reactions
Open Research DataThe equilibrium constants (K) of reforming reactions in SOFC were supplied with this dataset
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublicationRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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Deep eutectic solvents based assay for extraction and determination of zinc in fish and eel samples using FAAS
PublicationA new assay based on effective (high recovery) extraction by means of deep eutectic solvents (DESs) was developed for ppb level determination of zinc in fishes and eel samples. Choline chloride and Phenol in a 1:2 M ratio was selected as optimal DES-based extraction solvent. 8-Hydroxy quinoline was used as a chelating agent for zinc ions. The optimized conditions were found at pH value of 8, ligand concentration of 10 mg/L, THF...
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Independent dynamics of slow, intermediate, and fast intracranial EEG spectral activities during human memory formation
PublicationA wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various low and high frequencies are spatiotemporally coordinated across the human brain during memory processing is inconclusive. They can either be coordinated together across a wide range of the frequency spectrum or induced in specific bands. We used a large dataset of human intracranial electroencephalography...
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Independent dynamics of slow, intermediate, and fast intracranial EEG spectral activities during human memory formation
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Wspomaganie komunikacji w procesie neurorehabilitacji z wykorzystaniem śledzenia wzroku i analizy sygnałów EEG
PublicationW pracy przedstawiono charakterystykę systemu do wspomagania komunikacji w procesie neurorehabilitacji osób w stanie ograniczonej świadomości. Przygotowana aplikacja komputerowa wykorzystuje metodę śledzenia wzroku wspomaganą analizą sygnału EEG. W pracy podano genezę powstania systemu, scharakteryzowano zaimplementowane ćwiczenia oraz pozostałe funkcjonalności, a także zamieszczono wyniki wstępnych badań dokonanych w kilku polskich...
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EEG data recorded in three mental states
Open Research DataElectroencephalographic (EEG) signals were acquired from 17 (14 males, 3 females) participants aged between 20 and 30 years.
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Informatika i ee Primeneniya
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Independent dynamics of low, intermediate, and high frequency spectral intracranial EEG activities during human memory formation
PublicationA wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various frequency ranges are coordinated across the space of the human cortex and time of memory processing is inconclusive. They can either be coordinated together across the frequency spectrum at the same cortical site and time or induced independently in particular bands. We used a large dataset of human intracranial...
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Wykorzystanie rzeczywistego zapisu EEG w modelu potencjałów wywołanych do testowania algorytmów detekcji potencjałów wzrokowych.
PublicationPrzedstawiona praca dotyczy kontynuacji badań modelowych, gdzie syntetyczna aktywność spontaniczna została zastąpiona sygnałem rzeczywistym. Ocenie podlega uprzednio stworzony model aktywności spontanicznej. Weryfikacji ulega przydatność algorytmu detekcji.
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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EE-ISAC—Practical Cybersecurity Solution for the Energy Sector
PublicationA recent survey of cybersecurity assessment methods proposed by the scientific community revealed that their practical adoption constitutes a great challenge. Further research that aimed at identifying the reasons for that situation demonstrated that several factors influence the applicability, including the documentation level of detail, the availability of supporting tools, and the continuity of support. This paper presents the...
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First detection of Herpesvirus anguillae (AngHV‐1) associated with mortalities in farmed giant mottled eel (Anguilla marmorata) in Vietnam
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Annales Universitatis Mariae Curie-Sklodowska Sectio EEE Horticultura
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Implementacja wykrywalnych usług typu REST na platformie Jakarta EE
PublicationNiniejszy rozdział przedstawia propozycję w jaki sposób może być realizowana implementacja wykrywalnych usług sieciowych opartych na stylu architektonicznym REST na platformie Jakarta EE. Zostały tutaj przedstawione zarówno podstawy teoretyczne niezależne od zastosowanej platformy technologicznej, jak i szczegóły implementacji w technologii JAX-RS wchodzącej w skład platformy Jakarta EE. W szczególności zostały tutaj przedstawione...
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Fast and Efficient Four-Class Motor Imagery EEG Signals Analysis Using CSP-Ridge Regression Algorithm for the Purpose of Brain-Computer Interface."
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Detection of Herpesvirus anguillae (AngHV‐1) in European eel Anguilla anguilla (L.) originating from northern Poland—assessment of suitability of selected diagnostic methods
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What Potential Entrepreneurs from Generation Y and Z Lack-IEO and the Role of EE
PublicationThis paper addresses the issue of individual entrepreneurship orientation (IEO) and entrepreneurship education (EE), which are both important for modern economic development. Intergenerational differences in these areas were discussed, especially characteristics of Generations Y and Z. The results of research conducted among 757 Polish students showing their IEO are presented. 80% of respondents displayed high levels of proactivity...
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The set of 22 sessions of 14-channel eeg signals recorded during watching pictures
Open Research DataThe data were collected in order to perform research on the possibility of controlling the content displayed on the monitor screen using human emotional states extracted from EEG signals. The dataset contains recordings of 14-channel EEG signals collected from 10 persons within 22 sessions, during which 45 different random photos taken from the ImageNet...
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New potential functions for greedy independence and coloring
PublicationA potential function $f_G$ of a finite, simple and undirected graph $G=(V,E)$ is an arbitrary function $f_G : V(G) \rightarrow \mathbb{N}_0$ that assigns a nonnegative integer to every vertex of a graph $G$. In this paper we define the iterative process of computing the step potential function $q_G$ such that $q_G(v)\leq d_G(v)$ for all $v\in V(G)$. We use this function in the development of new Caro-Wei-type and Brooks-type...
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The PolarScreen™ Estrogen Receptor Competitor Assays for determination of estradiol equivalent concentrations (EEQs) in sewage and drinking water samples.
Open Research DataMunicipal waste waters are one of the main sources of estrogenic compounds in aquatic environments. Feminization of fish downstream of Waste Water Treatment Plants (WWTPs) discharges has been observed worldwide. Some estrogenic chemicals, particularly steroid estrogens, are known to cause disruption of the endocrine system of fishes and abnormalities...
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Annales Universitatis Mariae Curie-Skłodowska Sectio EE Zootechnica
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Measuring and Analyzing Audio Levels in Film, Commercials, and Movie Trailers Using Leq(A) Values and the LUFS Loudness Model . Analiza pomiarów dźwięku w filmie oraz w reklamach filmowych z wykorzystaniem modelu głośności
PublicationThe purpose of this paper is to describe the measurement of loudness levels in movies, movie trailers, and commercials displayed before feature films at movie theaters. In the initial section, the paper discusses the issues related to measurement of loudness levels, provides recommendations regarding permissible loudness levels during movie screenings, and mentions the applied units of measurement. The following section of the...