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  • Trade-off between real-time and classification performance in motor imagery BCI [Elektronski vir]
    Miladinović, Aleksandar ...
    Brain-Computer Interfaces (BCIs) offer direct communication between the brain and external devices, holding immense potential across various applications. This study focuses on Motor Imagery-based ... BCIs (MI-BCI), decoding neural patterns associated with mentally rehearsed motor actions. Despite their promise, BCIs face challenges in real-world applications, primarily in reliability and complexity. While classification accuracy is a standard metric for BCI performance, the literature often overlooks real-time responsiveness.Many studies report classification outcomes offline, disregarding the prompt translation of EEG signals into actions. The acceptable delay from EEG signal to action should not exceed 1 s; however, numerous studies employ time-windows exceeding 4 s, affecting user control perception. This article aims to compare the trade-off between timewindow length and classification accuracy in MI-BCI, using three linear classifiers (LDA, MLP, SVM). Participants include stroke patients and subjects from the BCI IVa dataset. Results demonstrate time-frequency plots indicating MI-related EEG changes, revealing a trade-off between accuracy and responsiveness. Our findings underscores the importance of addressing real-time responsiveness in BCI evaluations, proposing a balance for practical system utility. In conclusion, this study enhances our understanding of the delicate balance needed for optimal realworld application of MI-BCIs, emphasizing the trade-off between accuracy and responsiveness.
    Source: Proceedings of the EMBEC 2024 [Elektronski vir] : 9th European Medical and Biological Engineering Conference, June 9 - 13, 2024 Portorož, Slovenia. Vol. 2 (Str. 336-344)
    Type of material - conference contribution ; adult, serious
    Publish date - 2024
    Language - english
    COBISS.SI-ID - 199069443

    Link(s):

    https://link.springer.com/chapter/10.1007/978-3-031-61628-0_37
    DOI

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