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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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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
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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