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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Journal ArticleDOI
Long-term evaluation of a 4-class imagery-based brain-computer interface.
TL;DR: Users can control a real-time 4-class BCI, driven by distinct mental tasks, with stable performance over months, however, general performance was rather low for effective BCI control in daily life.
Journal ArticleDOI
Wireless EEG with individualized channel layout enables efficient motor imagery training
TL;DR: It is demonstrated that systematic MI practice in an everyday environment with a user-friendly EEG system results in MI learning effects and helps to bridge the gap between elaborate laboratory studies with healthy participants and efficient home or hospital based MI neurofeedback protocols.
Journal ArticleDOI
ℓ1-penalized linear mixed-effects models for high dimensional data with application to BCI
TL;DR: A large set of brain computer interface data is studied and through the novel estimator a subject-independent classifier is obtained that compares favorably with prior zero-training algorithms and a deeper understanding both of the underlying statistical and physiological structures of the data is gained.
Journal ArticleDOI
Summary of over Fifty Years with Brain-Computer Interfaces-A Review.
Aleksandra Kawala-Sterniuk,Natalia Browarska,Amir F. Al-Bakri,Mariusz Pelc,Mariusz Pelc,Jarosław Zygarlicki,Michaela Sidikova,Radek Martinek,Edward Jacek Gorzelanczyk +8 more
TL;DR: In this paper, the authors present the most relevant aspects of the BCI and all the milestones that have been made over nearly 50-year history of this research domain and highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many.
Proceedings ArticleDOI
A feasibility study of non-invasive motor-imagery BCI-based robotic rehabilitation for Stroke patients
Chuanchu Wang,Kok Soon Phua,Kai Keng Ang,Cuntai Guan,Haihong Zhang,Rongsheng Lin,Karen Sui Geok Chua,Beng Ti Ang,Christopher Wee Keong Kuah +8 more
TL;DR: The results show that most BCI-naïve hemiparetic stroke patients are capable of operating the BCI effectively, hence motivates further clinical studies on the extent of howBCI-based robotic rehabilitation are comparable with the control group that uses only robotic rehabilitation.
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.