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A wearable group-synchronized EEG system for multi-subject brain-computer interfaces.

Yong Huang1,2, Yuxiang Huan2, Zhuo Zou3

  • 1School of Biomedical Engineering, Southern Medical University, Guangzhou, China.

Frontiers in Neuroscience
|August 4, 2023
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Summary

This study introduces a wireless system for synchronized neural recording, enabling real-time multi-subject brain-computer interface (mBCI) analysis. The system achieves high accuracy and low noise, advancing group behavior research.

Keywords:
collaborative intelligencegroup-synchronizedhyperscanningmulti-subject brain–computer interfacereal-timereal-time group-synchronizedwearable

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Multi-subject brain-computer interfaces (mBCI) are crucial for analyzing group behaviors.
  • Current neural recording systems often rely on fixed wires, limiting collaborative acquisition.
  • There is a need for advanced systems supporting real-time, synchronized neural data collection for groups.

Purpose of the Study:

  • To design and evaluate a wireless, group-synchronized neural recording system.
  • To enable real-time mBCI and event-related potential (ERP) analysis for multiple subjects simultaneously.
  • To overcome limitations of wired systems in collaborative brain signal acquisition.

Main Methods:

  • Developed a wireless synchronizer broadcasting events to multiple wearable EEG amplifiers.
  • Implemented data packet marking for real-time event correlation analysis in groups.
  • Conducted collaborative signal sampling with 10 wireless mBCI devices.

Main Results:

  • Achieved high average signal correlation (99.8%) and low average noise amplitude (0.87 μV).
  • Demonstrated minimal synchronization error (237 μs) and high common mode rejection ratio (109.02 dB).
  • Attained competitive information transfer rates (150 ± 20 bits/min) and high accuracy (98%) in SSVEP-based BCI tasks, comparable to leading systems.

Conclusions:

  • The developed system is a high-performance tool for real-time mBCI research.
  • It facilitates advanced analysis of group behaviors and neural synchrony.
  • The system is poised to enable future applications in collaborative intelligence, cognitive neurology, and rehabilitation.