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. Neural oscillations during motor imagery of complex gait: an HdEEG study. Sci Rep. 2022;12(1):4314.
. 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). Causal influence of gamma oscillations on the sensorimotor rhythm. Neuroimage [Internet]. 2011;56(2):837-42. http://www.ncbi.nlm.nih.gov/pubmed/20451626 Causal influence of gamma oscillations on the sensorimotor rhythm.pdf (949.65 KB)
Causal influence of gamma oscillations on the sensorimotor rhythm.pdf (949.65 KB). Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery. J Neural Eng [Internet]. 2011;8(3):036005. http://www.ncbi.nlm.nih.gov/pubmed/21474878 Closing the sensorimotor loop haptic feedback facilitates decoding of motor imagery.pdf (1.81 MB)
Closing the sensorimotor loop haptic feedback facilitates decoding of motor imagery.pdf (1.81 MB). Voluntary brain regulation and communication with electrocorticogram signals. Epilepsy Behav [Internet]. 2008;13(2):300-6. http://www.ncbi.nlm.nih.gov/pubmed/18495541 Voluntary brain regulation and communication with electrocorticogram signals.pdf (1.45 MB)
Voluntary brain regulation and communication with electrocorticogram signals.pdf (1.45 MB). A µ-rhythm Matched Filter for Continuous Control of a Brain-Computer Interface. IEEE Trans Biomed Eng [Internet]. 2007;54(2):273-80. http://www.ncbi.nlm.nih.gov/pubmed/17278584 A mu-Rhythm Matched Filter for Continuous Control of a Brain-Computer Interface.pdf (0 bytes)
A mu-Rhythm Matched Filter for Continuous Control of a Brain-Computer Interface.pdf (0 bytes). 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). ECoG factors underlying multimodal control of a brain-computer interface. IEEE Trans Neural Syst Rehabil Eng [Internet]. 2006;14(2):246-50. http://www.ncbi.nlm.nih.gov/pubmed/16792305 wilson2006.pdf (912.69 KB)
wilson2006.pdf (912.69 KB). Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology [Internet]. 2005;64(10):1775-7. http://www.ncbi.nlm.nih.gov/pubmed/15911809 Patients with ALS can use sensorimotor rhythms to operate a brain-comptuer interface.pdf (0 bytes)
Patients with ALS can use sensorimotor rhythms to operate a brain-comptuer interface.pdf (0 bytes). A brain-computer interface using electrocorticographic signals in humans. J Neural Eng [Internet]. 2004;1(2):63-71. http://www.ncbi.nlm.nih.gov/pubmed/15876624 A brain-computer interface using electrocorticographic signals in humans.pdf (0 bytes)
A brain-computer interface using electrocorticographic signals in humans.pdf (0 bytes)