Investigation of physiological characteristics and coupling mechanism between EMG and EEG in motor intensity tasks

The brain-computer interface (BCI) technique could accelerate the progress of neural plasticity for patient with central nerve injury. However, research on motion recognition with different intensity is not sufficiently compared with gesture recognition. This paper mainly explores the physiological characteristics of electroencephalography (EEG) and electromyography (EMG) signals and their synergistic mechanism features under different intensity levels. The event-related de-synchronization/synchronization (ERD/ERS) information based on EEG signal and the synergistic mechanism of EEG and EMG signals using transfer entropy were sequentially analyzed. Experiments were performed on the data captured from three subjects to study the ERD/ERS and coupling mechanism in different intensity levels. Results showed that the ERD/ERS phenomenon was more obvious and the transfer entropy was bigger in high-intensity task, compared with low-intensity task. The results indicate that there is a strong coupling relationship between the cerebral cortex and muscle when performing or imagining high-intensity task.

• Publication year

  2022

• Venue

  CME

• Publication date

  2022-11-04

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/CME55444.2022.10063304
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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