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EEG signal is highly dynamic and hence it becomes extremely complicated to identify patterns embedded in the EEG signal. Moreover it may get contaminated by the various artifacts. EEG signal consist of different bands and each of these bands corresponds to different mental activity. In this research, patterns corresponding to the mental imaginations are extracted. Frequency band corresponding to the motor imagination is in the Beta range and hence used for extracting the hidden patterns. In this article the patterns are categorized utilizing latency and amplitude parameters at different ERP components. These identified patterns can be utilized to build assistive devices for disabled. Four class Motor Imagination (MI) database, 2a from BCI competition IV is used to reveal the patterns in the EEG signal. It is found that these patterns vary from MI activity to activity and from user to user.

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Identification of EEG Patterns Corresponding to Movement Imagination for Assistive Applications

  • 会议论文

  • 发表日期：

    2026年

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  • Snehal V. Dongare,
  • Dinesh V. Padole

摘要

EEG signal is highly dynamic and hence it becomes extremely complicated to identify patterns embedded in the EEG signal. Moreover it may get contaminated by the various artifacts. EEG signal consist of different bands and each of these bands corresponds to different mental activity. In this research, patterns corresponding to the mental imaginations are extracted. Frequency band corresponding to the motor imagination is in the Beta range and hence used for extracting the hidden patterns. In this article the patterns are categorized utilizing latency and amplitude parameters at different ERP components. These identified patterns can be utilized to build assistive devices for disabled. Four class Motor Imagination (MI) database, 2a from BCI competition IV is used to reveal the patterns in the EEG signal. It is found that these patterns vary from MI activity to activity and from user to user.