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Search results for: 14-channel EEG signal
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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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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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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_004)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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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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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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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublicationIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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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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Analysis of radiometric signal in sedimentating suspension flow in open channel
PublicationThe article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most...
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Probe signal processing for channel estimation in underwater acoustic communication system
PublicationUnderwater acoustic communication channels are characterized by a large variety of propagation conditions. Designing a reliable communication system requires knowledge of the transmission parameters of the channel, namely multipath delay spread, Doppler spread, coherence time, and coherence bandwidth. However, the possibilities of its estimation in a realtime underwater communication system are limited, mainly due to the computational...
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Neural Oscillation During Mental Imagery in Sport: An Olympic Sailor Case Study
PublicationThe purpose of the current study was to examine the cortical correlates of imagery depending on instructional modality (guided vs. self-produced) using various sports-related scripts. According to the expert-performance approach, we took an idiosyncratic perspective analyzing the mental imagery of an experienced two-time Olympic athlete to verify whether different instructional modalities of imagery (i.e., guided vs. self-produced)...
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Study of probe signal bandwidth influence on estimation of coherence bandwidth for underwater acoustic communication channel
PublicationA signal transmitted in a shallow Underwater Acoustic Communication (UAC) channel suffers from time dispersion due to the multipath propagation and the refraction phenomena. This causes intersymbol interference of the received signal and frequency-selective fading observed in its spectrum. Coherence bandwidth is one of the key transmission parameters used for designing the physical layer of a data transmission system to minimise...
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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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Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal
PublicationThe performances of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Designing the physical layer of a reliable data transmission system requires a knowledge of channel characteristics in terms of the specific parameters of the stochastic model. The Wide-Sense Stationary Uncorrelated Scattering (WSSUS) assumption simplifies the stochastic description...
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A New Direct-Sequence Spread Spectrum Signal Detection Method for Underwater Acoustic Communications in Shallow-Water Channel
PublicationDirect-Sequence Spread Spectrum (DSSS) is one of the modulation and coding techniques used in Underwater Acoustic Communication (UAC) systems for reliable data transmision even at low signal levels. However, in a shallow water channel, there is a strong multipath propagation which causes a phase fluctuation of the received signal, affecting the performance of the spread-spectrum system. The article presents a differential method...
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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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Wiktoria Wojnicz dr hab. inż.
PeopleDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) List of papers (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis of...
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Jacek Stefański prof. dr hab. inż.
PeopleJJacek Stefański received M.Sc., Ph.D. and D.Sc. degrees in telecommunications engineering from Gdansk University of Technology (GUT), Poland, in 1993, 2000 and 2012, respectively. Awarded title of Professor by the President of Poland in 2020. Currently, he works as a professor at the Department of Radio Communication Systems and Networks (DRCSN) in GUT. From 2005 to 2009, he worked as an assistant professor in the National Institute...
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Marek Blok dr hab. inż.
PeopleMarek Blok in 1994 graduated from the Faculty of Electronics at Gdansk University of Technology receiving his MSc in telecommunications. In 2003 received Ph.D. and in 2017 D.Sc. in telecommunications from the Faculty of Electronics, Telecommunications and Informatics of Gdańsk University of Technology. His research interests are focused on application of digital signal processing in telecommunications. He provides lectures, laboratory...
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Comparison of selected electroencephalographic signal classification methods
PublicationA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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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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TIME- AND FREQUENCY-DOMAIN QUASI-2D SMALL-SIGNAL MOSFET MODELS
PublicationA novel approach to small-signal MOSFET modeling is presented in this book. As a result, time- and frequency-domain physics-based quasi-2D NQS four-terminal small-signal MOSFET models are proposed. The time-domain model provides the background to a novel DIBL-included quasi‑2D NQS four-terminal frequency-domain small-signal MOSFET model. Parameters and electrical quantities of the frequency-domain model are described by explicit...
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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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A quasi-2D small-signal MOSFET model - main results
PublicationDynamic properties of the MOS transistor under small-signal excitation are determined by kinetic parameters of the carriers injected into the channel, i.e., the low-field mobility, velocity saturation, mobility at the quiescent-point (Q-point), longitudinal electric field in the channel, by dynamic properties of the channel, as well as by an electrical coupling between the perturbed carrier concentration in the channel and the...
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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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Estimation of Coherence Bandwidth for Underwater Acoustic Communication Channel
PublicationA shallow underwater acoustic communication channel is characterized by strong multipath propagation. The signal reaching the receiver consists of a direct waveform and a number of its delayed and suppressed replica. A significant time dispersion of the transmitted signal and selective fading of its spectrum are observed. Coherence bandwidth defines maximal bandwidth, wherein the channel amplitude characteristic remains constant...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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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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A Simplistic Downlink Channel Estimation Method for NB-IoT
PublicationThis paper presents a downlink channel estimation method intended for a Narrowband Internet of Things (NB-IoT) access link. Due to its low computational complexity, this method is well suited for energy-efficient IoT devices, still providing acceptable reception quality in terms of signal-to-noise (SNR) performance. This paper describes the physical layer of NB-IoT within the scope of channel estimation, and also reviews existing...
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Reduction of the Multipath Propagation Effect in a Hydroacoustic Channel Using Filtration in Cepstrum
PublicationDuring data transmission in a hydroacoustic channel, one of the problems is the multipath propagation effect, which leads to a decrease in the transmission parameters and sometimes completely prevents it. Therefore, we have attempted to develop a method, which is based on a recorded hydroacoustic signal, that allows us to recreate the original (generated) signal by eliminating the multipath effect. In our method, we use cepstral...
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The Influence of the Radio Channel on Precision of Position Estimation of the User Terminal Using the NB-IoT Radio Interface
PublicationIn the article the method of user terminal position estimation using the broadcast signals transmitted in the downlink of the NB-IoT interface was presented, including the analysis of the radio channel influence on precision of position estimation as well as the eNodeB (Evolved Node B) synchronization. The practical ability to estimate the position in the test area has been verified in the laboratory conditions, using the reference...
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Selected properties and parameters of radio channel impulse response estimation in ISM 2.4 GHz band
PublicationThe article presents experimental research indicating that the impulse response of the communication channel, determined in practice, are not of an universal character, but only represent its approximate value for the frequency on which this measurement was made. Phases for each of the replicas of the measurement signal were determined during the analysis of the received signals in the baseband. Phase changes of individual replicas...
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A simplified channel estimation procedure for NB-IoT downlink
PublicationThis paper presents a low-complexity channel estimation procedure which is suitable for use in energy-efficient NB-IoT user equipment devices. The procedure is based on the well-established least squares scheme, followed by linear interpolation in the time domain and averaging in the frequency domain. The quality of channel estimation vs. signal-to-noise ratio is evaluated for two channel models and compared with the performance...
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Simulation of Direct-Sequence Spread Spectrum Data Transmission System for Reliable Underwater Acoustic Communications
PublicationUnderwater acoustic communication (UAC) system designers tend to transmit as much information as possible, per unit of time, at as low as possible error rate. It is a particularly difficult task in a shallow underwater channel in which the signal suffers from strong time dispersion due to multipath propagation and refraction phenomena. The direct-sequence spread spectrum technique (DSSS) applied successfully in the latest standards...
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A Quasi-2D MOSFET Model — 2D-to-Quasi-2D Transformation
PublicationA quasi-two-dimensional (quasi-2D) representation of the MOSFET channel is proposed in this work. The representation lays the foundations for a quasi 2D MOSFET model. The quasi 2D model is a result of a 2D into quasi 2D transformation. The basis for the transformation are an analysis of a current density vector field and such phenomena as Gradual Channel Detachment Effect (GCDE), Channel Thickness Modulation Effect (CTME), and...
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Testing the Wide-Sense Stationarity of Bandpass Signals for Underwater Acoustic Communications
PublicationThe Underwater Acoustic Communication (UAC) systems work in communication channels characterized by a large variety of multipath propagation conditions that can additionally change over time. Designing a reliable communication system requires knowledge of the transmission parameters of the channel. There is a need for the development of adaptive signaling schemes that would dynamically optimize the signal parameters of the physical...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Detection of dialogue in movie soundtrack for speech intelligibility enhancement
PublicationA method for detecting dialogue in 5.1 movie soundtrack based on interchannel spectral disparity is presented. The front channel signals (left, right, center) are analyzed in the frequency domain. The selected partials in the center channel signal, which yield high disparity with left and right channels, are detected as dialogue. Subsequently, the dialogue frequency components are boosted to achieve increased dialogue intelligibility....
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Instantaneous complex frequency for pipeline pitch estimation
PublicationIn the paper a pipeline algorithm for estimating the pitch of speech signal is proposed. The algorithm uses instantaneous complex frequencies estimated for four waveforms obtained by filtering the original speech signal through four bandpass complex Hilbert filters. The imaginary parts of ICFs from each channel give four candidates for pitch estimates. The decision regarding the final estimate is made based on the real parts of...
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Estymacja parametrów kanału NB-IoT w łączu w dół.
PublicationArtykuł dotyczy doboru metody estymacji parametrów kanału, odpowiedniej do zastosowania w terminalu wąskopasmowego Internetu Rzeczy. Przedstawiono strukturę sygnału pilotowego NRS, używanego do wyznaczenia współczynników kanału w LTE-NB. Zaproponowano cztery warianty metody wyznaczenia współczynników kanału dla całej ramki transmisyjnej. Dokonano oceny tych wariantów w oparciu o dwa wskaźniki jakościowe skojarzone z błędem odtworzonych...
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Adrian Kastrau mgr inż.
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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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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Improving listeners' experience for movie playback through enhancing dialogue clarity in soundtracks
PublicationThis paper presents a method for improving users' quality of experience through processing of movie soundtracks. The dialogue clarity enhancement algorithms were introduced for detecting dialogue in movie soundtrack mixes and then for amplifying the dialogue components. The front channel signals (left, right, center) are analyzed in the frequency domain. The selected partials in the center channel signal, which yield high disparity...
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Daytime Acute Non-Visual Alerting Response in Brain Activity Occurs as a Result of Short- and Long-Wavelengths of Light
PublicationVery recent preliminary findings concerning the alerting capacities of light stimulus with long-wavelengths suggest the existence of neural pathways other than melatonin suppression that trigger the nonvisual response. Though the nonvisual effects of light during the daytime have not been investigated thoroughly, they are definitely worth investigating. The purpose of the present study is to enrich existing evidence by describing...
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Suppression of distortions in signals received from Doppler sensor for vehicle speed measurement
PublicationDoppler sensors are commonly used for movement detection and speed measurement. However, electromagnetic interference and imperfections in sensor construction result in degradation of the signal to noise ratio. As a result, detection of signals reflected from moving objects becomes problematic. The paper proposes an algorithm for reduction of distortions and noise in the signal received from a simple, dual-channel type of a Doppler...
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An Empirical Model for the Polarisation Characteristics of Indoor Off-Body Channels
PublicationThis paper presents an analysis of the polarisation characteristics for the channel in dynamic off-body communications, and an empirical channel model, based on measurements performed at 2.45 GHz in an office environment. Body presence and propagation conditions have a strong influence on signal depolarisation. The model assumes three components for the total path loss: mean path loss, represented by a log-distance function with...
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ADAPTIVE IDENTIFICATION OF TIME-VARYING IMPULSE RESPONSE OF UNDERWATER ACOUSTIC COMMUNICATION CHANNEL
PublicationThe transmission properties of underwater acoustic communication channel can change dynamically due to the movement of acoustic system transmitter and receiver or underwater objects reflecting transmitted signal. The time-varying impulse response measurement and estimation are necessary to match the physical layer of data transmission to instantaneous channel propagation conditions. Using the correlative measurement method, impulse...
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Wideband Off-Body Channel Characteristics with Dynamic User
PublicationThis paper presents the preliminary results of a dynamic off-body channel characterisation study, based on wideband measurements at 5.8 GHz in an indoor environment. The Channel Impulse Response (CIR) was measured for a scenario with the user approaching and departing from the off-body antenna. A CIR deconvolution procedure was performed jointly in two polarisations, and the received signal power, Cross-Polarisation Discrimination...
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Measurements of transmission properties of Acoustic Communication Channels
PublicationTough transmission properties of shallow water acoustic channels (SWAC) highly limit the use of underwater acoustic communication (UAC) systems. An adaptive matching of modulation and signaling schemes to instantaneous channel conditions is needed for reliabledata communications. This creates, however, unique challenges for designers when compared to radio transmission systems. When communication system elements are in move, the...
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Measurement of Impulse Response of Shallow Water Communication Channel by Correlation Method
PublicationPerformances of underwater acoustic communication (UAC) systems are strongly related to specific propagation conditions of the underwater channel; conditions that can additionally change in time due to the movement of the acoustic system transmitter and receiver or to reflection by underwater objects of the transmitted signal. The time-varying impulse response is a comprehensive description of dynamically changing transmission...