Enhanced Online Continuous Brain-Control by Deep Learning-based EEG Decoding.

Journal: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Published Date: Jul 21, 2025

Abstract

OBJECTIVE: A growing amount of deep learning models for motor imagery (MI) decoding from electroencephalogram (EEG) have demonstrated their superiority over traditional machine learning approaches in offline dataset analysis. However, current online MI-based brain-computer interfaces (BCIs) still predominantly adopt machine learning decoders while falling short of high BCI performance. Yet, the generalization and advantages of deep learning-based EEG decoding in realistic BCI systems remain far unclear.

Authors

  • Jiaheng Wang
    School of Computer Science, Zhejiang Universty, Hangzhou 310000, P.R.China.
  • Lin Yao
    School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.
  • Yueming Wang

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals