Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface

—In motor imagery-based Brain Computer Interfaces (BCI), discriminative patterns can be extracted from the electroencephalogram (EEG) using the Common Spatial Pattern (CSP) algorithm. However, the performance of this spatial filter depends on the operational frequency band of the EEG. Thus, setting a broad frequency range, or manually selecting a subject-specific frequency range, are commonly used with the CSP algorithm. To address this problem, this paper proposes a novel Filter Bank Common Spatial Pattern (FBCSP) to perform autonomous selection of key temporalspatial discriminative EEG characteristics. After the EEG measurements have been bandpass-filtered into multiple frequency bands, CSP features are extracted from each of these bands. A feature selection algorithm is then used to automatically select discriminative pairs of frequency bands and corresponding CSP features. A classification algorithm is subsequently used to classify the CSP features. A study is conducted to assess...

• Type: Conference
• Year: 2008
• Where: IJCNN
• Authors: Kai Keng Ang, Zhang Yang Chin, Haihong Zhang, Cuntai Guan
• Keywords: Artificial Intelligence, Classification Algorithm, CSP Features, Frequency Bands, IJCNN 2008