Journal ArticleDOI
The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects.
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TLDR
It is proposed that the key to quick efficiency in the BBCI system is its flexibility due to complex but physiologically meaningful features and its adaptivity which respects the enormous inter-subject variability.About:
This article is published in NeuroImage.The article was published on 2007-08-15. It has received 865 citations till now. The article focuses on the topics: Brain–computer interface.read more
Citations
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Proceedings ArticleDOI
A waypoint-based framework in brain-controlled smart home environments: Brain interfaces, domotics, and robotics integration
Atsunori Kanemura,Yoichi Morales,Motoaki Kawanabe,Hiroshi Morioka,Nagasrikanth Kallakuri,Tetsushi Ikeda,Takahiro Miyashita,Norihiro Hagita,Shin Ishii +8 more
TL;DR: A BMI framework that combines BMI with a robotic house and autonomous robotic wheelchair is proposed and experimented and is an excellent examples of the fusion of data measured by sensors in the house, which can offer insight into further studies.
Book ChapterDOI
Brain-Computer Interface and Motor Imagery Training: The Role of Visual Feedback and Embodiment
TL;DR: The results from a series of experiments in which users BCI-operated a humanlike android robot confirm that realistic visual feedback can induce a sense of embodiment, which promotes a significant learning of the motor imagery task in a short amount of time.
Optimal Transport Applied to Transfer Learning For P300 Detection
TL;DR: Results show that the transfer learning method based on regularized discrete optimal transport with class labels is comparable to-and sometimes even outperforms-session-dependent classification.
Journal ArticleDOI
Enhancing sensorimotor BCI performance with assistive afferent activity: An online evaluation
Carmen Vidaurre,Carmen Vidaurre,A. Ramos Murguialday,Stefan Haufe,Marisol Gómez,Klaus-Robert Müller,Klaus-Robert Müller,Klaus-Robert Müller,Vadim V. Nikulin,Vadim V. Nikulin,Vadim V. Nikulin +10 more
TL;DR: Online experiments confirmed accuracy improvement of MI alone being decoded with the classifier trained on BOTH data and observed that the performance in MI condition could be predicted on the basis of a more pronounced connectivity within sensorimotor areas in the frequency bands providing the best performance in BOTH.
Proceedings ArticleDOI
Robust common spatial filters with a maxmin approach
TL;DR: This work presents two ways of calculating robust common spatial patterns under a maxmin approach and compares their results with the classical common spatial filters and shows that both can improve the performance of the latter.
References
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Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
Journal ArticleDOI
Brain-computer interfaces for communication and control.
Jonathan R. Wolpaw,Jonathan R. Wolpaw,Niels Birbaumer,Niels Birbaumer,Dennis J. McFarland,Gert Pfurtscheller,Theresa M. Vaughan +6 more
TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
Journal ArticleDOI
Event-related EEG/MEG synchronization and desynchronization: basic principles.
TL;DR: Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously.