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Comparison of Adaptive Spatial Filters with Heuristic and Optimized Region of Interest for EEG Based Brain-Computer-Interfaces

2007

Conference Paper

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Research on EEG based brain-computer-interfaces (BCIs) aims at steering devices by thought. Even for simple applications, BCIs require an extremely effective data processing to work properly because of the low signal-to-noise-ratio (SNR) of EEG signals. Spatial filtering is one successful preprocessing method, which extracts EEG components carrying the most relevant information. Unlike spatial filtering with Common Spatial Patterns (CSP), Adaptive Spatial Filtering (ASF) can be adapted to freely selectable regions of interest (ROI) and with this, artifacts can be actively suppressed. In this context, we compare the performance of ASF with ROIs selected using anatomical a-priori information and ASF with numerically optimized ROIs. Therefore, we introduce a method for data driven spatial filter adaptation and apply the achieved filters for classification of EEG data recorded during imaginary movements of the left and right hand of four subjects. The results show, that in the case of artifact-free datasets, ASFs with numerically optimized ROIs achieve classification rates of up to 97.7 % while ASFs with ROIs defined by anatomical heuristic stay at 93.7 % for the same data. Otherwise, with noisy datasets, the former brake down (66.7 %) while the latter meet 95.7 %.

Author(s): Liefhold, C. and Grosse-Wentrup, M. and Gramann, K. and Buss, M.
Book Title: Pattern Recognition
Journal: Pattern Recognition: 29th DAGM Symposium
Pages: 274-283
Year: 2007
Month: September
Day: 0
Editors: Hamprecht, F. A., C. Schn{\"o}rr, B. J{\"a}hne
Publisher: Springer

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1007/978-3-540-74936-3_28
Event Name: 29th Annual Symposium of the German Association for Pattern Recognition
Event Place: Heidelberg, Germany

Address: Berlin, Germany
Digital: 0
Institution: DAGM
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{4984,
  title = {Comparison of Adaptive Spatial Filters with Heuristic and Optimized Region of Interest for EEG Based Brain-Computer-Interfaces},
  author = {Liefhold, C. and Grosse-Wentrup, M. and Gramann, K. and Buss, M.},
  journal = {Pattern Recognition: 29th DAGM Symposium},
  booktitle = {Pattern Recognition},
  pages = {274-283},
  editors = {Hamprecht, F. A., C. Schn{\"o}rr, B. J{\"a}hne},
  publisher = {Springer},
  organization = {Max-Planck-Gesellschaft},
  institution = {DAGM},
  school = {Biologische Kybernetik},
  address = {Berlin, Germany},
  month = sep,
  year = {2007},
  month_numeric = {9}
}