The brain response interface: communication through visually-induced electrical brain responses
Journal of Microcomputer Applications - Special issue on computers for handicapped people
Fitts' law as a performance model in human-computer interaction
Fitts' law as a performance model in human-computer interaction
Brain-computer interface: a new communication device for handicapped persons
Journal of Microcomputer Applications - Special issue on computer applications for handicapped persons
The nature of statistical learning theory
The nature of statistical learning theory
Future multimedia user interfaces
Multimedia Systems - Special issue on tutorials and surveys
Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Multimodal human discourse: gesture and speech
ACM Transactions on Computer-Human Interaction (TOCHI)
Single Trial Detection of EEG Error Potentials: A Tool for Increasing BCI Transmission Rates
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Proceedings of Gesture Workshop on Progress in Gestural Interaction
Designing human-computer interfaces for quadriplegic people
ACM Transactions on Computer-Human Interaction (TOCHI)
Towards an odor communication system
Computational Biology and Chemistry
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Editorial: Ambient intelligence: From interaction to insight
International Journal of Human-Computer Studies
Magnitude squared of coherence to detect imaginary movement
EURASIP Journal on Advances in Signal Processing - Special issue on statistical signal processing in neuroscience
Brain Computer Interfaces for inclusion
Proceedings of the 1st Augmented Human International Conference
The Berlin brain-computer interface
WCCI'08 Proceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers
Classification of single trial EEG based on cloud model for brain-computer interfaces
LSMS'07 Proceedings of the 2007 international conference on Life System Modeling and Simulation
International Journal of Autonomous and Adaptive Communications Systems
Time domain parameters for online feedback fNIRS-based brain-computer interface systems
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
BCI-based navigation in virtual and real environments
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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The investigation of innovative Human-Computer Interfaces (HCI) provides a challenge for future interaction research and development. Brain-Computer Interfaces (BCIs) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as amyotrophic lateral sclerosis (ALS) or complete paralysis of all extremities due to high spinal cord injury. Beyond medical applications, a BCI conjunction with exciting multimedia applications, e.g., a dexterity discovery, could define a new level of control possibilities also for healthy customers decoding information directly from the user's brain, as reflected in EEG signals which are recorded non-invasively from the scalp. This contribution introduces the Berlin Brain-Computer Interface (BBCI) and presents set-ups where the user is provided with intuitive control strategies in plausible interactive bio-feedback applications. Yet at its beginning, BBCI thus adds a new dimension in HCI research by offering the user an additional and independent communication channel based on brain activity only. Successful experiments already yielded inspiring proofs-of-concept. A diversity of interactive application models, say computer games, and their specific intuitive control strategies are now open for BCI research aiming at a further speed up of user adaptation and increase of learning success and transfer bit rates. BBCI is a complex distributed software system that can be run on several communicating computers responsible for (i) the signal acquisition, (ii) the data processing and (iii) the feedback application. Developing a BCI system, special attention must be paid to the design of the feedback application that serves as the HCI unit. This should provide the user with the information about her/his brain activity in a way that is intuitively intelligible. Exciting discovery applications qualify perfectly for this role. However, most of these applications incorporate control strategies that are developed especially for the control with haptic devices, e.g., joystick, keyboard or mouse. Therefore, novel control strategies should be developed for this purpose that (i) allow the user to incorporate additional information for the control of animated objects and (ii) do not frustrate the user in the case of a misclassification of the decoded brain signal. BCIs are able to decode different information types from the user's brain activity, such as sensory perception or motor intentions and imaginations, movement preparations, levels of stress, workload or task-related idling. All of these diverse brain signals can be incorporated in an exciting discovery scenario. Modern HCI research and development technologies can provide BCI researchers with the know-how about interactive feedback applications and corresponding control strategies.