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    This study introduces a novel visual Brain-Computer Interface (BCI) that allows users to spell by looking at environmental targets, not just flickers. This flexible BCI system achieves high accuracy and information transfer rates, simplifying setup for wider applications.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Human-Computer Interaction

    Background:

    • Conventional visual Brain-Computer Interfaces (BCIs) achieve high information transfer rates (ITRs) but suffer from limited user experience and complex setups.
    • The need to tag each target with a unique stimulus restricts the flexibility of existing visual BCI systems.
    • A more adaptable approach is needed to improve usability and broaden BCI applications.

    Purpose of the Study:

    • To propose and evaluate a novel method for flexible target decoding in visual BCIs.
    • To develop a BCI speller that allows users to control the system by looking at environmental symbols, bypassing the need to focus on specific stimuli.
    • To assess the accuracy and information transfer rates of this new BCI paradigm.

    Main Methods:

    • A BCI speller was developed with thirteen paper-drawn symbols interspersed with four flickers of distinct frequencies.
    • Subjects were instructed to spell sequences by looking at the symbols, not the flickers.
    • Performance was evaluated using cue-guided and free-spelling tasks, with analysis of a simulated online system.

    Main Results:

    • The cue-guided spelling task achieved average offline and online accuracies of 89.3±7.3% and 90.3±6.9%, respectively.
    • Corresponding information transfer rates (ITRs) were 43.0±7.4 bit/min (offline) and 43.8±6.8 bit/min (online).
    • A free-spelling task yielded 92.3±3.1% accuracy and 45.6±3.3 bit/min ITR. Simulated online analysis suggested potential ITRs of 105.8 bit/min with reduced epoch duration.

    Conclusions:

    • Reliable Brain-Computer Interface control is achievable by focusing on environmental targets rather than dedicated stimuli.
    • The proposed method significantly reduces the technical complexity of visual BCIs.
    • This advancement holds promise for expanding the practical applications of BCIs beyond laboratory settings.