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Decoding Finger Flexion using amplitude modulation from band-specific ECoG

Nanying Liang 1, * Laurent Bougrain 1 
* Corresponding author
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : EEG-BCIs have been well studied in the past decades and implemented into several famous applications, like P300 speller and wheelchair controller. However, these interfaces are indirect due to low spatial resolution of EEG. Recently, direct ECoG-BCIs attract intensive attention because ECoG provides a higher spatial resolution and signal quality. This makes possible localization of the source of neural signals with respect to certain brain functions. In this article, we present a realization of ECoG-BCIs for finger flexion prediction provided by BCI competition IV. Methods for finger flexion prediction including feature extraction and selection are provided in this article. Results show that the predicted finger movement is highly correlated with the true movement when we use band-specific amplitude modulation.
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Submitted on : Friday, July 31, 2009 - 11:56:46 AM
Last modification on : Friday, February 4, 2022 - 3:15:47 AM
Long-term archiving on: : Tuesday, June 15, 2010 - 7:18:23 PM


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  • HAL Id : inria-00408595, version 1
  • ARXIV : 0907.5500



Nanying Liang, Laurent Bougrain. Decoding Finger Flexion using amplitude modulation from band-specific ECoG. European Symposium on Artificial Neural Networks - ESANN 2009, Apr 2009, Bruges, Belgium. pp.467-472. ⟨inria-00408595⟩



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