Wyniki wyszukiwania dla: ELECTROENCEPHALOGRAM (EEG) - MOST Wiedzy

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Wyniki wyszukiwania dla: ELECTROENCEPHALOGRAM (EEG)
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Wyniki wyszukiwania dla: ELECTROENCEPHALOGRAM (EEG)

  • CLINICAL EEG AND NEUROSCIENCE

    Czasopisma

    ISSN: 1550-0594 , eISSN: 2169-5202

  • Balance recognition on the basis of EEG measurement.

    Although 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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  • Labeler-hot Detection of EEG Epileptic Transients

    Publikacja

    - Rok 2019

    Preventing 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.

    Przegląd 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.

  • Tensor Decomposition for Imagined Speech Discrimination in EEG

    Publikacja

    - LECTURE NOTES IN COMPUTER SCIENCE - Rok 2018

    Most 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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  • Transfer learning in imagined speech EEG-based BCIs

    Publikacja

    - Biomedical Signal Processing and Control - Rok 2019

    The 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

    Publikacja
    • A. Kastrau
    • M. Koronowski
    • M. Liksza
    • P. Jasik

    - Rok 2021

    This 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,...

  • Systematic Literature Review for Emotion Recognition from EEG Signals

    Publikacja

    Researchers 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

    Publikacja

    Researchers 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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  • Comparison of the effectiveness of automatic EEG signal class separation algorithms

    In 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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