Search results for: ELECTROENCEPHALOGRAM (EEG) - Bridge of Knowledge

Search

Search results for: ELECTROENCEPHALOGRAM (EEG)
Przykład wyników znalezionych w innych katalogach

Search results for: ELECTROENCEPHALOGRAM (EEG)

  • CLINICAL EEG AND NEUROSCIENCE

    Journals

    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....

    Full text available to download

  • 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.

  • Decoding imagined speech for EEG-based BCI

    Publication
    • C. A. Reyes-García
    • A. A. Torres-García
    • T. Hernández-del-Toro
    • J. S. Garcia Salinas
    • L. Villaseñor-Pineda

    - Year 2024

    Brain–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...

    Full text to download in external service

  • Tensor Decomposition for Imagined Speech Discrimination in EEG

    Publication

    - LECTURE NOTES IN COMPUTER SCIENCE - Year 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...

    Full text to download in external service

  • Labeler-hot Detection of EEG Epileptic Transients

    Publication

    - Year 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...

    Full text to download in external service

  • Transfer learning in imagined speech EEG-based BCIs

    Publication

    - Biomedical Signal Processing and Control - Year 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...

    Full text available to download

  • Systematic Literature Review for Emotion Recognition from EEG Signals

    Publication

    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...

    Full text available to download

  • Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion

    Publication

    The 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....

    Full text available to download

  • Automatic Clustering of EEG-Based Data Associated with Brain Activity

    The 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....

    Full text to download in external service