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Content Provider | IEEE Xplore Digital Library |
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Author | Feifei Qi Yuanqing Li Wei Wu |
Copyright Year | 2014 |
Description | Author affiliation: Sch. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China (Feifei Qi; Yuanqing Li; Wei Wu) |
Abstract | Common Spatial Patterns (CSP) is among the most popular spatial filtering methods used in motor imagery based brain-computer interfaces (BCIs). In this paper, a novel algorithm termed spatio-temporally regularized common spatial patterns (STR-CSP) is proposed to enhance CSP such that discriminative spatio-temporal EEG patterns can be extracted. Unlike most previous CSP-based spatio-temporal filtering algorithms in which spatial and temporal filters are optimized in a sequential manner, STR-CSP optimizes spatio-temporal filters simultaneously under a unified criterion with analytical solutions. Moreover, the algorithm enables us to alleviate the over-fitting problem by L2-norm regularization. Successful application to the analysis of a BCI competition EEG data set comprising 18 subsets demonstrates the superiority of STR-CSP over contemporary methods. |
Starting Page | 7212 |
Ending Page | 7215 |
File Size | 1324138 |
Page Count | 4 |
File Format | |
ISBN | 9789881563873 |
ISSN | 19341768 |
DOI | 10.1109/ChiCC.2014.6896192 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-07-28 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | TCCT, CAA |
Subject Keyword | Algorithm design and analysis combined spatio-temporal filter motor imagery (MI) Electroencephalography Brain-computer interfaces Brain-Computer Interface (BCI) common spatial patterns (CSP) Optimization electroencephalography (EEG) Accuracy Finite impulse response filters l2-norm regularization Eigenvalues and eigenfunctions |
Content Type | Text |
Resource Type | Article |
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