An approach to extracting features of movement-related potentials based on neighborhood spatial pattern

作者：Liu, Mei-Chun^*; Zhao, Min; Xie, Sheng-Li

来源：Journal of South China University of Technology(Natural Science Edition), 2009, 37(10): 11-15.

• Classification algorithm
• Data distribution
• Electroencephalogram (EEG) datum
• Event related desynchronization
• Extracting features
• Important features
• Movement related potentials
• Neighborhood

In order to remedy the complex distribution of recorded electroencephalogram (EEG) data and the shortage of training data in terms of brain-computer interface (BCI), a novel approach named neighborhood spatial pattern (NSP) is proposed to extract movement-related potentials (MRPs), which constitute the most important features utilized in the classification algorithms for the motor-imagery-based BCI. NSP searches the optimal direction which maximizes the ratio of the between-class distance to the within-class distance of the neighborhood in the projected space. During the search, no assumptions about the latent data distribution should be made, and only the neighborhood relationship and the label information are required. NSP is also applied to two datasets from BCI competitions 2003 and 2001. The results show that NSP can effectively extract MPRs features.

• 出版日期2009-10
• 单位华南理工大学