Channel Selection for Multi-class Motor Imagery Based on Common Spatial Pattern / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 520-525, 2015.
Article
Dans Chinois
| WPRIM
| ID: wpr-359614
ABSTRACT
High-density channels are often used to acquire electroencephalogram (EEG) spatial information in different cortical regions of the brain in brain-computer interface (BCI) systems. However, applying excessive channels is inconvenient for signal acquisition, and it may bring artifacts. To avoid these defects, the common spatial pattern (CSP) algorithm was used for channel selection and a selection criteria based on norm-2 is proposed in this paper. The channels with the highest M scores were selected for the purpose of using fewer channels to acquire similar rate with high density channels. The Dataset III a from BCI competition 2005 were used for comparing the classification accuracies of three motor imagery between whole channels and the selected channels with the present proposed method. The experimental results showed that the classification accuracies of three subjects using the 20 channels selected with the present method were all higher than the classification accuracies using all 60 channels, which convinced that our method could be more effective and useful.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Algorithmes
/
Reconnaissance physiologique des formes
/
Électroencéphalographie
/
Interfaces cerveau-ordinateur
Type d'étude:
Étude pronostique
Limites du sujet:
Humains
langue:
Chinois
Texte intégral:
Journal of Biomedical Engineering
Année:
2015
Type:
Article
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