Decoding of Grasp Motions from EEG Signals Based on a Novel Data Augmentation Strategy

Jeong Hyun Cho, Ji Hoon Jeong, Seong Whan Lee

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)

    Abstract

    Electroencephalogram (EEG) based braincomputer interface (BCI) systems are useful tools for clinical purposes like neural prostheses. In this study, we collected EEG signals related to grasp motions. Five healthy subjects participated in this experiment. They executed and imagined five sustained-grasp actions. We proposed a novel data augmentation method that increases the amount of training data using labels obtained from electromyogram (EMG) signals analysis. For implementation, we recorded EEG and EMG simultaneously. The data augmentation over the original EEG data concluded higher classification accuracy than other competitors. As a result, we obtained the average classification accuracy of 52.49(±8.74)% for motor execution (ME) and 40.36(±3.39)% for motor imagery (MI). These are 9.30% and 6.19% higher, respectively than the result of the comparable methods. Moreover, the proposed method could minimize the need for the calibration session, which reduces the practicality of most BCIs. This result is encouraging, and the proposed method could potentially be used in future applications such as a BCI-driven robot control for handling various daily use objects.

    Original languageEnglish
    Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
    Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3015-3018
    Number of pages4
    ISBN (Electronic)9781728119908
    DOIs
    Publication statusPublished - 2020 Jul
    Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
    Duration: 2020 Jul 202020 Jul 24

    Publication series

    NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    Volume2020-July
    ISSN (Print)1557-170X

    Conference

    Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
    Country/TerritoryCanada
    CityMontreal
    Period20/7/2020/7/24

    Bibliographical note

    Publisher Copyright:
    © 2020 IEEE.

    ASJC Scopus subject areas

    • Signal Processing
    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Health Informatics

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