BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 1. General architecture of an online (BCI)
| Main Authors: | Dalila Trad, Tarik Al-Ani, Mohamed Jemni |
|---|---|
| Format: | info Image eJournal |
| Bahasa: | eng |
| Terbitan: |
, 2016
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| Subjects: | |
| Online Access: |
https://www.edusoft.ro/brain/index.php/brain/article/view/591/652 |
Daftar Isi:
- One major challenge of our BCI system is to describe the signals EEG by a few relevant values called features i.e. step 3 in Fig (1). The success of the mental imagery classification depends on the choice of features used to characterize the raw EEG signals. These features can then be used in step 4 in order to classify the user’s mental state. Several approaches for feature extraction have been proposed in literature.