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  • The contribution investigates the impact of frequency feature optimization on discriminating between movement-related EEG realisations associated with right shoulder elevation and right index finger flexion movements. Exhaustive search of subbands in the range from 5 to 45 Hz is performed. A classifier based on Hidden Markov Models is utilised. The results show a large variability of optimal settings among subjects and electrodes. Using subband optimization an average 3.5 % increase in classification accuracy of EEG filtered using 8-neighbor Laplacian filter was achieved, reaching an overall score of 81.2 +- 1.2 %, individual improvements ranging from 1.2 to 9.9 %. The best general setting common for all subject was confirmed as 5-40 Hz.
  • The contribution investigates the impact of frequency feature optimization on discriminating between movement-related EEG realisations associated with right shoulder elevation and right index finger flexion movements. Exhaustive search of subbands in the range from 5 to 45 Hz is performed. A classifier based on Hidden Markov Models is utilised. The results show a large variability of optimal settings among subjects and electrodes. Using subband optimization an average 3.5 % increase in classification accuracy of EEG filtered using 8-neighbor Laplacian filter was achieved, reaching an overall score of 81.2 +- 1.2 %, individual improvements ranging from 1.2 to 9.9 %. The best general setting common for all subject was confirmed as 5-40 Hz. (en)
Title
  • Subband Optimization for EEG-based Classification of Movements of the Same Limb
  • Subband Optimization for EEG-based Classification of Movements of the Same Limb (en)
skos:prefLabel
  • Subband Optimization for EEG-based Classification of Movements of the Same Limb
  • Subband Optimization for EEG-based Classification of Movements of the Same Limb (en)
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  • RIV/68407700:21230/14:00223190!RIV15-MSM-21230___
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  • 48417
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  • RIV/68407700:21230/14:00223190
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  • BCI; EEG; HMM; Movement EEG classification (en)
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  • [3D52258112D6]
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  • Pilsen
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  • Pilsen
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  • 19th International Conference on Applied Electronics 2014
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  • Šťastný, Jakub
  • Dobiáš, Martin
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issn
  • 1803-7232
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/AE.2014.7011671
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  • Západočeská univerzita v Plzni
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  • 978-80-261-0276-2
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  • 21230
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