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Motor Imagery Classification for BCI Using Common Spatial Patterns and Feature Relevance Analysis.

, , and . IWINAC (2), volume 7931 of Lecture Notes in Computer Science, page 365-374. Springer, (2013)

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Multiple Instance Learning Selecting Time-Frequency Features for Brain Computing Interfaces., , , and . IWAIPR, volume 11047 of Lecture Notes in Computer Science, page 326-333. Springer, (2018)Relevance of Common Spatial Patterns Ranked by Kernel PCA in Motor Imagery Classification., , , , , and . BI, volume 11976 of Lecture Notes in Computer Science, page 13-20. Springer, (2019)An Enhanced Joint Hilbert Embedding-Based Metric to Support Mocap Data Classification with Preserved Interpretability., , , , and . Sensors, 21 (13): 4443 (2021)Deep and Wide Transfer Learning with Kernel Matching for Pooling Data from Electroencephalography and Psychological Questionnaires., , , , and . Sensors, 21 (15): 5105 (2021)Feature relevance analysis supporting automatic motor imagery discrimination in EEG based BCI systems., , and . EMBC, page 7068-7071. IEEE, (2013)Detecting EEG Dynamic Changes Using Supervised Temporal Patterns., , , and . IWAIPR, volume 11047 of Lecture Notes in Computer Science, page 351-358. Springer, (2018)Group Differences in Time-Frequency Relevant Patterns for User-Independent BCI Applications., , , , and . IWINAC (1), volume 11486 of Lecture Notes in Computer Science, page 138-145. Springer, (2019)Time-series discrimination using feature relevance analysis in motor imagery classification., , and . Neurocomputing, (2015)Entropy-Based Estimation of Event-Related De/Synchronization in Motor Imagery Using Vector-Quantized Patterns., , and . Entropy, 22 (6): 703 (2020)Subject-Oriented Dynamic Characterization of Motor Imagery Tasks Using Complexity Analysis., , and . BI, volume 11976 of Lecture Notes in Computer Science, page 21-28. Springer, (2019)