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ORIGINAL RESEARCH article

Front. Hum. Neurosci.
Sec. Brain-Computer Interfaces
Volume 18 - 2024 | doi: 10.3389/fnhum.2024.1461960

Four-class ASME BCI: investigation of the feasibility and comparison of two strategies for multiclassing

Provisionally accepted
  • Shibaura Institute of Technology, Minato, Tōkyō, Japan

The final, formatted version of the article will be published soon.

    The ASME (stands for Auditory Stream segregation Multiclass ERP) paradigm is proposed and used for an auditory brain-computer interface (BCI). In this paradigm, a sequence of sounds that are perceived as multiple auditory streams are presented simultaneously, and each stream is an oddball sequence. The users are requested to focus selectively on deviant stimuli in one of the streams, and the target of the user attention is detected by decoding event-related potentials (ERPs). To achieve multiclass ASME BCI, the number of streams must be increased.However, increasing the number of streams is not easy because of a person's limited audible frequency range. One method to achieve multiclass ASME with a limited number of streams is to increase the target stimuli in a single stream.Methods Two approaches for the ASME paradigm, ASME-4stream (four streams with a single target stimulus in each stream) and ASME-2stream (two streams with two target stimuli in each stream) were investigated. Fifteen healthy subjects with no neurological disorders participated in this study. An electroencephalogram was acquired, and ERPs were analyzed. The binary classification and BCI simulation (detecting the target class of the trial out of four) were conducted with the help of linear discriminant analysis, and its performance was evaluated offline. Its usability and workload were also evaluated using a questionnaire.Discriminative ERPs were elicited in both paradigms. The average accuracies of the BCI simulations were 0.83 (ASME-4stream) and 0.86 (ASME-2stream). In the ASME-2stream paradigm, the latency and the amplitude of P300 were shorter and larger, the average binary classification accuracy was higher, and the average weighted workload was smaller.Discussion Both four-class ASME paradigms achieved a sufficiently high accuracy (over 80%).The shorter latency and larger amplitude of P300 and the smaller workload indicated that subjects could perform the task confidently and had high usability in ASME-2stream compared to ASME-4stream paradigm. A paradigm with multiple target stimuli in a single stream could create a multiclass ASME BCI with limited streams while maintaining task difficulty. These findings expand the potential for an ASME BCI multiclass extension, offering practical auditory BCI choices for users.

    Keywords: Brain-computer interface, Electroencephalogram, event-related potential, auditory scene analysis, stream segregation, machine learning, NASA-TLX

    Received: 09 Jul 2024; Accepted: 28 Oct 2024.

    Copyright: © 2024 Kojima and Kanoh. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Simon Kojima, Shibaura Institute of Technology, Minato, 108-8548, Tōkyō, Japan

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.