Journal ArticleDOI
The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects.
Reads0
Chats0
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
More filters
Book ChapterDOI
Brain-Computer Interfaces and Visual Activity
TL;DR: What is known about the effects of visual stimuli on brain activity is presented and means of monitoring brain activity are introduced and possibilities of brain‐controlled interfaces, either with the brain signals as the sole input or in combination with the measured point of gaze, are discussed.
Journal ArticleDOI
An Adaptive Calibration Framework for mVEP-Based Brain-Computer Interface
TL;DR: Experimental results demonstrate that the adaptive calibration framework for the brain-computer interface with the motion-onset visual evoked potential as the control signal is effective and efficient and it could improve the performance of online BCI systems.
Patent
Method for controlling or regulating a machine
TL;DR: In this paper, a contactless man/machine interface and an appropriate method for controlling or regulating a machine is presented. But the interface comprises a first signal generator, which is equipped with at least one component that has a noise signal.
Posted Content
Emotion visualization in Virtual Reality: An integrative review.
Andres Pinilla Palacios,Jaime A. Garcia,William L. Raffe,Jan-Niklas Voigt-Antons,Robert P. Spang,Sebastian Möller +5 more
TL;DR: A review of previous studies from these fields to understand how to develop virtual environments that can automatically create visual representations of users' emotional states and theories related to emotion and affect are compared.
Journal ArticleDOI
Knowledge-driven feature component interpretable network for motor imagery classification
TL;DR: In this article , a knowledge-driven feature component interpretable network (KFCNet) is proposed, which combines spatial and temporal convolution in analogy to independent component analysis and a power spectrum pipeline.
References
More filters
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.