A classification-based method to estimate event-related potentials from single trial EEG

A novel method based on machine learning is developed to estimate event-related potentials from single trial electroencephalography. This paper builds a basic framework using classification and an optimization model based on this framework for estimating event-related potentials. Then the SingleTrialEM algorithm is derived by introducing a logistic regression model, which could be obtained by training before SingleTrialEM is used, to instantiate the optimization model. The simulation tests demonstrate that the proposed method is correct and solid. The advantage of this method is verified by the comparison between this method and the Woody filter in simulation tests. Also, the cognitive test results are consistent with the conclusions of cognitive science.

• Publication year

  2012

• Venue

  Science China Life Sciences

• Publication date

  2012-01-01

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1007/s11427-011-4263-xPMID 22314492
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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