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Improving single-hand open/close motor imagery classification by error-related potentials correction.

Yanghao Lei1,2, Dong Wang1,2, Weizhen Wang1,2

  • 1Institute of Robotics and Intelligent System, School of Mechanical Engineering, Xi'an Jiaotong University, Xi' an,710049, China.

Heliyon
|July 31, 2023
PubMed
Summary

This study introduces a hybrid brain-computer interface (BCI) using error-related potentials (ErrP) to improve motor imagery (MI) classification accuracy for single-hand tasks.

Keywords:
Brain computer interfaceCorrection strategyElectroencephalogramError-related potentialsMotor imagery

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Brain-computer interfaces (BCI) classify electroencephalogram (EEG) signals for motor imagery (MI) tasks.
  • Classifying single-hand open/close MI tasks is challenging due to overlapping cortical activity.
  • Improving BCI accuracy is crucial for effective human-computer interaction.

Purpose of the Study:

  • To enhance the classification accuracy of single-hand MI tasks in BCIs.
  • To introduce a hybrid BCI paradigm integrating error-related potentials (ErrP) with MI.
  • To develop a strategy for correcting MI classification using ErrP information.

Main Methods:

  • A hybrid BCI paradigm combining ErrP and MI was designed.
  • EEG data from 11 subjects performing single-hand open/close MI tasks were analyzed.
  • ErrP and MI features were superimposed, and a correction strategy was applied.

Main Results:

  • The proposed correction strategy significantly improved classification accuracy for single-hand open/close MI tasks.
  • Classification accuracy increased from 52.3% to 73.7%, a 21% improvement.
  • The integration of ErrP information enhanced the BCI's performance.

Conclusions:

  • The hybrid BCI paradigm effectively improves single-hand MI classification accuracy.
  • Adding ErrP information provides a novel approach to enhance BCI performance.
  • This strategy offers a promising direction for advancing BCI technology.