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Movement EEG Classification Using Parallel Hidden Markov Models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00301765" target="_blank" >RIV/68407700:21230/16:00301765 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/AE.2016.7577243" target="_blank" >http://dx.doi.org/10.1109/AE.2016.7577243</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/AE.2016.7577243" target="_blank" >10.1109/AE.2016.7577243</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Movement EEG Classification Using Parallel Hidden Markov Models

  • Original language description

    In this contribution we examine the use and utility of parallel HMM classification in single-trial movement-EEG classification of index finger reaching and grasping movement. Parallel HMMs allow us to easily utilize the information contained in multiple channels. Using HMM classifier output in parallel from examined EEG channels we have been able to achieve as good a classification score as with single electrode results, further we do not rely on a single electrode giving persistently good results. Our parallel approach has the added benefit of not having to rely on small inter-session variability as it gives very good results with fewer classifier parameters being optimized. Without any classification optimization we can get a score improvement of 11.2% against randomly selected physiologically relevant electrode. If we use subject specific information we can further improve on the reference score by 1%, achieving a classification score of 84.2+-0.7%.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2016 International Conference on Applied Electronics

  • ISBN

    978-80-261-0601-2

  • ISSN

    1803-7232

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    65-68

  • Publisher name

    University of West Bohemia

  • Place of publication

    Pilsen

  • Event location

    Plzeň

  • Event date

    Sep 6, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000391238700014