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Issue No.10 - October (2008 vol.41)
pp: 44-50
Alois Schlögl , Graz University of Technology
Clemens Brunner , Graz University of Technology
ABSTRACT
The lack of common tools and standards has made software development a key issue in brain-computer interface research. With the BioSig project's tool repository, brain-computer interface researchers can avoid reinventing the wheel on every project.
INDEX TERMS
brain-computer interface, biomedical signal processing, neuroinformatics, medical informatics
CITATION
Alois Schlögl, Clemens Brunner, "BioSig: A Free and Open Source Software Library for BCI Research", Computer, vol.41, no. 10, pp. 44-50, October 2008, doi:10.1109/MC.2008.407
REFERENCES
1. J.R. Wolpaw et al., "Brain-Computer Interfaces for Communication and Control," Clinical Neurophysiology, June 2002, pp. 767–791.
2. G. Pfurtscheller et al., "Separability of EEG Signals Recorded during Right and Left Motor Imagery Using Adaptive Autoregressive Parameters," IEEE Trans. Rehabilitation Eng., Sept. 1998, pp. 316–325.
3. B. Blankertz et al., "Optimizing Spatial Filters for Robust EEG Single-Trial Analysis," IEEE Signal Processing Magazine, Jan. 2008, pp. 41–56.
4. B. Blankertz et al., "The BCI Competition 2003: Progress and Perspectives in Detection and Discrimination of EEG Single Trials," IEEE Trans. Biomedical Eng., June 2004, pp. 1044–1051.
5. B. Blankertz et al., "The BCI Competition III: Validating Alternative Approaches to Actual BCI Problems," IEEE Trans. Neural Systems and Rehabilitation Eng., June 2006, pp. 153–159.
6. C. Vidaurre et al., "Study of On-line Adaptive Discriminant Analysis for EEG-Based Brain Computer Interfaces," IEEE Trans. Biomedical Eng., Mar. 2007, pp. 550–556.
7. S.G. Mason and G.E. Birch, "A Brain-Controlled Switch for Asynchronous Control Applications," IEEE Trans. Biomedical Eng., Oct. 2000, pp. 1297–1307.
8. H. Ramoser, J. Müller-Gerking, and G. Pfurtscheller, "Optimal Spatial Filtering of Single Trial EEG during Imagined Hand Movement," IEEE Trans. Rehabilitation Eng., Dec. 2000, pp. 441–446.
9. A. Schlögl et al., "Quality Control of Polysomnographic Sleep Data by Histogram and Entropy Analysis," Clinical Neurophysiology, Dec. 1999, pp. 2165–2170.
10. B.S. Oken, "Filtering and Aliasing of Muscle Activity in EEG Frequency Analysis," Electroencephalography and Clinical Neurophysiology, July 1986, pp. 77–80.
11. A. Schlögl et al., "A Fully Automated Correction Method of EOG Artifacts in EEG Recordings," Clinical Neurophysiology, Jan. 2007, pp. 98–104.
12. M. Krauledat et al., "Reducing Calibration Time for Brain-Computer Interfaces: A Clustering Approach," Proc. 20th Ann. Conf. Advances in Neural Information Processing Systems (NIPS 06), MIT Press, 2007, pp. 753–760.
13. G. Pfurtscheller et al., "On-line EEG Classification during Externally-Paced Hand Movements Using a Neural Network-Based Classifier," Electroencephalography and Clinical Neurophysiology, Oct. 1996, pp. 416–425.
14. C. Guger et al., "Rapid Prototyping of an EEG-Based Brain-Computer Interface (BCI)," IEEE Trans. Neural Systems and Rehabilitation Eng., Mar. 2001, pp. 49–58.
15. C. Vidaurre and A. Schlögl, "Comparison of Adaptive Features with Linear Discriminant Classifier for Brain Computer Interfaces," to appear in Proc. 30th Ann. Int'l Conf. IEEE Eng. in Medicine and Biology Society (EMBS 07), IEEE Press, 2008.
16. A. Schlögl, The Electroencephalogram and the Adaptive Autoregressive Model: Theory and Applications, Shaker Verlag, 2000.
17. A. Schlögl, C. Neuper, and G. Pfurtscheller, "Subject-Specific EEG Pattern during Motor Imagery," Proc. 19th Ann. Int'l Conf. IEEE Eng. Medicine and Biology Society (EMBS 97), IEEE Press, 1997, pp. 1530–1532.
18. D. Flotzinger, J. Kalcher, and G. Pfurtscheller, "EEG Classification by Learning Vector Quantization," Biomedizinische Technik, Dec. 1992, pp. 303–309.
19. R. Scherer et al., "The Self-Paced Graz Brain-Computer Interface: Methods and Applications," Computational Intelligence and Neuroscience, Jan. 2007; www.aksioma.org/brainloop/txtcomputational_intelligence_neuroscience.pdf .
20. R. Scherer et al., "Towards Self-Paced Brain-Computer Communication: Navigation through Virtual Worlds," IEEE Trans. Biomedical Eng., Feb. 2008, pp. 675–682.
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