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. Adaptive spatio-temporal filtering for movement related potentials in EEG-based brain-computer interfaces. IEEE Trans Neural Syst Rehabil Eng [Internet]. 2014;22(4):847-57. http://www.ncbi.nlm.nih.gov/pubmed/24723632
Adaptive spatio-temporal filtering for movement related potentials in EEG-based brain-computer interfaces.pdf (1.81 MB)
Adaptive spatio-temporal filtering for movement related potentials in EEG-based brain-computer interfaces.pdf (1.81 MB). A graphical model framework for decoding in the visual ERP-based BCI speller. Neural Comput [Internet]. 2011;23(1):160-82. http://www.ncbi.nlm.nih.gov/pubmed/20964540 A graphical model framework for decoding in the visual ERP-based BCI speller.pdf (443.32 KB)
A graphical model framework for decoding in the visual ERP-based BCI speller.pdf (443.32 KB). Seizure prediction for epilepsy using a multi-stage phase synchrony based system. Conf Proc IEEE Eng Med Biol Soc [Internet]. 2009;2009:25-8. http://www.ncbi.nlm.nih.gov/pubmed/19965104 james2009.pdf (730.49 KB)
james2009.pdf (730.49 KB). Particle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification. J Struct Biol [Internet]. 2008;164(1):41-8. http://www.ncbi.nlm.nih.gov/pubmed/18619547 Particle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification.pdf (2.75 MB)
Particle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification.pdf (2.75 MB). Space-time ICA versus Ensemble ICA for ictal EEG analysis with component differentiation via Lempel-Ziv complexity. Conf Proc IEEE Eng Med Biol Soc [Internet]. 2007;08/2007:5473-6. http://www.ncbi.nlm.nih.gov/pubmed/18003250 james2007.pdf (608.27 KB)
james2007.pdf (608.27 KB). Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects. IEEE Trans Neural Syst Rehabil Eng [Internet]. 2006;14(2):183-6. http://www.ncbi.nlm.nih.gov/pubmed/16792289 Classifying EEG and ECoG signals without subject training for fast BCI implementation comparison of nonparalyzed and completely paralyzed subjects.pdf (56.97 KB)
Classifying EEG and ECoG signals without subject training for fast BCI implementation comparison of nonparalyzed and completely paralyzed subjects.pdf (56.97 KB). The BCI Competition 2003: Progress and perspectives in detection and discrimination of EEG single trials. IEEE Trans Biomed Eng. 2004;51(6):1044-51. The BCI Compeition 2003 - Progress and Perspectives in Detection and Discrimination of EEG Single Trials.pdf (0 bytes)
The BCI Compeition 2003 - Progress and Perspectives in Detection and Discrimination of EEG Single Trials.pdf (0 bytes)