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We present a general approach to the development of an unobtrusive and fast passive braincomputer interface that could be deeply integrated with gaze based control for fluent translation of intentions into actions, as well as the results of a pilot test of its online version in 9 healthy participants. The new hybrid Eye-Brain-Computer Interface (EBCI) utilizes an electroencephalogram component presumably related to the expectation of feedback from the gaze controlled interface. Online operation of the EBCI was made possible using Resonance, a new platform for fast prototyping of BCIs, enabling fast synchronized processing of multimodal signals from varying hardware with scripts written in R. In the online mode, EBCI provided the result of 19 channel EEG classification almost immediately when gaze dwell on a screen object (a colored “ball”) exceeded 500 ms time threshold. For the first time, non-random online EBCI classifier performance was demonstrated.

Passive Detection of feedback Expectation: towards Fluent Hybrid eye-brain-Computer Interfaces