Adaptive feature extraction in EEG-based motor imagery BCI: tracking mental fatigue.

Journal: Journal of neural engineering
PMID: 31683268

Abstract

OBJECTIVE: Electroencephalogram (EEG) signals are non-stationary. This could be due to internal fluctuation of brain states such as fatigue, frustration, etc. This necessitates the development of adaptive brain-computer interfaces (BCI) whose performance does not deteriorate significantly with the adversary change in the cognitive state. In this paper, we put forward an unsupervised adaptive scheme to adapt the feature extractor of motor imagery (MI) BCIs by tracking the fatigue level of the user.

Authors

  • Upasana Talukdar
    Biomimetic & Cognitive Robotics Lab, Department of Computer Science & Engineering, Tezpur University, Tezpur, India. Author to whom any correspondence should be addressed.
  • Shyamanta M Hazarika
  • John Q Gan
    School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom.

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