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Improving the Classification of Olfactory Brain-Computer Interface Responses by Combining EEG and EBG Signals.

Hubert Kasprzak, Nina Niewinska, Tomasz Komendzinski

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    Summary

    This study introduces a novel olfactory brain-computer interface (BCI) using electroencephalography (EEG) and electrobulbography (EBG). Combining these methods improves the accuracy of classifying brain responses to scent stimuli.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Sensory Systems

    Background:

    • Brain-computer interfaces (BCIs) offer natural interaction with technology.
    • Olfaction (sense of smell) presents a unique modality for BCI enhancement.
    • Current olfactory BCIs face challenges in accurate odor delivery and brain signal interpretation.

    Purpose of the Study:

    • To develop and evaluate a novel olfactory brain-computer interface (BCI) modality.
    • To improve the classification accuracy of brain responses to olfactory stimuli.
    • To explore the combined use of electroencephalography (EEG) and electrobulbography (EBG) for olfactory BCI.

    Main Methods:

    • Utilized a classical oddball paradigm with six distinct scent stimuli.
    • Recorded brain activity using electroencephalography (EEG) and electrobulbography (EBG).
    • Applied Common Spatial Pattern (CSP) filtration to EEG and EBG data for signal processing.

    Main Results:

    • The combined EEG and EBG approach demonstrated promising results in pilot testing.
    • The proposed method showed improved classification accuracy for olfactory responses.
    • Successful classification of brain activity patterns associated with different scent stimuli was achieved.

    Conclusions:

    • The integration of EEG and EBG offers a viable new modality for olfactory BCIs.
    • This approach enhances the potential for naturalistic human-computer interaction via smell.
    • Further research is warranted to optimize odor delivery and BCI algorithms.