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Search results for: EEG SIGNAL ANALYSIS
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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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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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Tools for signal analysis of gas sensors
PublicationStatystyki drugiego rzedu oraz jklasyczna analiza widmowa są zwykle stosowane do badania sygnałów losowych o rozkładzie gaussowskim. Są one jednak często nieodpowiednie w przypadku analizy niestacjonarnych sygnałów niegaussowskich. Pewne narzędzia do analizy takich sygnałów sa dostępne w bibliotekach środowiska MATLAB. Zostały one wykorzystane do do analizy fluktuacji sygnałów czujników gazów. W artykule przedstawiono system do...
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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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The Use of Wavelet Analysis to Denoising of Electrocardiography Signal
PublicationThe electrocardiography examination, due to its accessibility and simplicity, has an important role in diagnostics of the heart ailments. It enables quick detection of various heart defects, undetectable by other kinds of diagnostic tools, so it is very popular. Nevertheless, the measured signal is exposed to a different disturbances. Among them, the electromagnetic interferences, drift of reference electrode and high frequency...
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General analysis of braodband signal spatial filtration.
PublicationPrzedstawiono ogólną metodę wyznaczania charakterystyk kierunkowych filtrów przestrzennych dla hydroakustycznych sygnałów przestrzennych. Omówiono wpływ szerokości widma odbieranych sygnałów na szerokość wiązki i poziom listków bocznych. Pokazano skutki oszczędnych metod filtracji przestrzennej stosowanych przy odbiorze sygnałów wąskopasmowych, gdy odbierane są sygnały szerokopasmowe.
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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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Analysis of allophones based on audio signal recordings and parameterization
PublicationThe aim of this study is to develop an allophonic description of English plosive consonants based on recordings of 600 specially selected words. Allophonic variations addressed in the study may have two sources: positional and contextual. The former one depends on the syllabic or prosodic position in which a particular phoneme occurs. Contextual allophony is conditioned by the local phonetic environment. Co-articulation overlapping...
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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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Advanced acoustic signal analysis used for wheel-flat detection
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Fiber optic displacement sensor with signal analysis in spectral domain
PublicationIn this paper, a study of a low-coherence fiber optic displacement sensor is presented. The sensor consisted of a broadband source whose central wavelength was either at 1310 nm or 1550 nm, a sensing Fabry-Pérot interferometer operating in reflective mode and an optical spectrum analyzer acting as the detection setup. All these components were connected by a single-mode fiber coupler. Metrological parameters of the sensor were...
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Analysis of Positioning Error and Its Impact on High Frequency Performance Parameters of Differential Signal Coupler of Differential Signal Coupler
PublicationThis paper presents the analysis of the effect of differential signal coupler positioning accuracy on its high frequency performance parameters for contact-less high speed chip-to-chip data transmission on PCB application. Our considerations are continuation of the previous works on differential signal coupler concept, design methodology and analysis for high speed data transmission monitoring presented in [1, 2]. The theoretical...
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Accuracy analysis of the RSSI BLE SensorTag signal for indoor localization purposes
PublicationIn this paper we describe possibility of use the RSSI signal (Radio Signal Strength Indication) from Texas Instruments SensorTag CC2650 for indoor positioning purposes. This idea is not a new but in our opinion it is possible to use SensorTags with Bluetooth LE wireless interface for positioning inside buildings in such applications as people findings in hospitals, senior come care, etc. RSSI is mostly selected as the sensor localization...
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Usage of the Gstreamer framework for generation, analysis, processing and visualization of sonar signal
PublicationIn this paper a novel method of the bearing estimation in a passive sonar system with a towed array is introduced. The classical approach of the bearing estimation based on the spatial spectrum is extended by using the synchrosqeezing method that is a part of the reassignment method introduced by Kodera et al. The usage of this method leads to the precise bearing estimation. The proposed method requires a relatively small amount...
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Implementation complexity analysis of the turbo decoding algorithms on digital signal processor
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Analysis of the torque response of a car engine to the step change of the control signal
PublicationW pracy zamieszczono wyniki badań silnika samochodu osobowego w warunkach nieustalonych. Stan obciążenia silnika wynikał z realizowanego cyklu jezdnego w warunkach drogowych oraz sposobu sterowania układem napędowym. Parametry trakcyjne pojazdu mierzone były za pomocą systemu GPS z fenomenologiczną korektą sygnału wysokości, na której się on znajdował. Wybrane parametry pracy silnika mierzone były za pomocą sytemu komunikującego...
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Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System
PublicationBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in...
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Methods of measurement signal acquisition from the rotational flow meter for frequency analysis
PublicationOne of the simplest and commonly used instruments for measuring the flow of homogeneous substances is the rotational flow meter. The main part of such a device is a rotor (vane or screw) rotating at a speed which is the function of the fluid or gas flow rate. A pulse signal with a frequency proportional to the speed of the rotor is obtained at the sensor output. For measurements in dynamic conditions, a variable interval between...
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Combined method of multibeam sonar signal processing and image analysis for seafloor classification
PublicationThe combined approach to seafloor characterisation was investigated. It relies on calculation of several descriptors (parameters) related to seabed type using three types of multibeam sonar data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive...
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Seafloor characterisation using multibeam sonar echo signal processing and image analysis
PublicationThe authors propose the approach to multibeam seafloor characterisation which relies on the combined, concurrent use of two different techniques of multibeam sonar data processing. The first one is based on constructing the grey-level sonar images of seabed using the echoes received in the consecutive beams. Then, the parameters describing the local region of sonar image, namely, the local standard deviation of a grey level, and...
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Analysis of positioning error and its impact on high frequency properties of differential signal coupler
PublicationThis paper presents the analysis of the effect of differential signal coupler positioning accuracy on its high frequency performance parameters for contact-less high speed chip-to-chip data transmission on PCB application. Our considerations are continuation of the previous works on differential signal coupler concept, design methodology and analysis for high speed data transmission monitoring. The theoretical analysis of possible...
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Application of gamma densitometry and statistical signal analysis to gas phase velocity measurements in pipeline hydrotransport
PublicationThe work presents selected methods of signal analysis used in the processing of data obtained from radiometric probes. The used data came from an exemplary study of a two-phase liquid-gas flow at the laboratory installation. In such rigs many possible transport types may be observed, i.e. slug, plug and bubble flow, and each of them gives different signal-to-noise ratio of recorded data. Therefore, available radiometric methods...
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Application of gamma densitometry and statistical signal analysis to gas phase velocity measurements in pipeline hydrotransport
PublicationThe work presents selected methods of signal analysis used in the processing of data obtained from radiometric probes. The used data came from an exemplary study of a two-phase liquid-gas flow at the laboratory installation. In such rigs many possible transport types may be observed, i.e. slug, plug and bubble flow, and each of them gives different signal-to-noise ratio of recorded data. Therefore, available radiometric methods...
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Analysis of Roughness, the Material Removal Rate, and the Acoustic Emission Signal Obtained in Flat Grinding Processes
PublicationIn this work, the analysis of the acoustic emission (AE) signal in grinding processes is addressed. The proposed analysis method decomposes the acoustic signal into three frequency ranges. The total energy of each range is determined, as well as the highest frequency. Different grinding experiments were carried out, according to a full factorial design of experiments (DOE), in which feed speed, depth of cut, and transversal step...
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seafloor characterisation combined approach using multibeam sonar echo signal processing and image analysis
PublicationThe authors propose the approach to seafloor characterisation which relies on the combined, concurrent use of two different techniques: (i) multibeam sonar image analysis and (ii) multibeam seabed echoes processing. The first technique is based on constructing the grey-level sonar images of the seabed extracted from the echoes received in the consecutive soundings. Then, the set of parameters describing the local region of sonar...
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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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Application of Time-Frequency Analysis of Acoustic Signal to Detecting Flat Places on the Rolling Surface of a Tram Wheel
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The effect of a polyharmonic structure of the perturbation signal on the results of harmonic analysis of the current of a first-order electrode reaction
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Multiparameter analysis of the Barkhausen noise signal and its application for the assessment of plastic deformation level in 13HMF grade steel
PublicationArtykuł przedstawia wyniki wieloparametrowej analizy właściwości sygnału szumu Barkhausena (BN). Poza powszechnie stosowanymi kwantyfikatorami sygnału szumu Barkhausena takimi jak amplituda, całka z obwiedni sygnału czy też wynikami analizy impulsowej sygnału proponujemy dodatkową analizę opartą na zmianach amplitudy prądu magnesującego. Jak się okazuje charakter zmian sygnału Barkhausena (w funkcji stopnia deformacji plastycznej)...
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Application of signal to noise ratio and grey relational analysis to minimize forces and vibrations during precise ball end milling
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Electric transport in organic system with planar DBP/F16ZnPc junction on the basis of direct current and small signal admittance spectra analysis
PublicationThe objective of this work was to determine electric transport in the organic device based on a planar junction of electron donor and electron acceptor materials, namely ITO/MoO3/DBP/F16ZnPc/BCP/Ag. The analysis reported herein was based on direct current-voltage measurements and small-signal admittance spectra in the dark and under illumination. Such analysis may provide information on potential barriers, parasitic resistances...
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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...