Self-organizing maps
Artificial Intelligence
Non-invasive brain-actuated control of a mobile robot
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A comparative psychophysical and EEG study of different feedback modalities for HRI
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Non-invasive brain-actuated interaction
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
The Berlin brain-computer interface
WCCI'08 Proceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers
Online detection of p300 and error potentials in a BCI speller
Computational Intelligence and Neuroscience - Special issue on processing of brain signals by using hemodynamic and neuroelectromagnetic modalities
Computers in Human Behavior
Computers in Biology and Medicine
On a NeuroIS design science model
DESRIST'11 Proceedings of the 6th international conference on Service-oriented perspectives in design science research
Trust in human-computer interactions as measured by frustration, surprise, and workload
FAC'11 Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systems
Pay attention!: designing adaptive agents that monitor and improve user engagement
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Detecting error-related negativity for interaction design
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
That's not norma(n/l): a detailed analysis of midas touch in gaze-based problem-solving
CHI '13 Extended Abstracts on Human Factors in Computing Systems
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Brain-computer interfaces, as any other interaction modality based on physiological signals and body channels (e.g., muscular activity, speech and gestures), are prone to errors in the recognition of subject's intent. In this paper we exploit a unique feature of the "brain channel", namely that it carries information about cognitive states that are crucial for a purposeful interaction. One of these states is the awareness of erroneous responses. Different physiological studies have shown the presence of error-related potentials (ErrP) in the EEG recorded right after people get aware they have made an error. However, for human-computer interaction, the central question is whether ErrP are also elicited when the error is made by the interface during the recognition of the subject's intent and no longer by errors of the subject himself. In this paper we report experimental results with three volunteer subjects during a simple human-robot interaction (i.e., bringing the robot to either the left or right side of a room) that seem to reveal a new kind of ErrP, which is satisfactorily recognized in single trials. These recognition rates significantly improve the performance of the brain interface.