Masking empirical mode decomposition-based hybrid features for recognition of motor imagery in EEG

No abstract is available for this paper.

• Publication year

  2017

• Venue

  International Conference Control Science and Systems Engineering

• Publication date

  2017-08-01

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1109/CCSSE.2017.8087992
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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  2015influential reference
• On the computational complexity of the empirical mode decomposition algorithm

  2014cited by this paper
• Phase space reconstruction for improving the classification of single trial EEG

  2014cited by this paper
• Efficient feature selection and linear discrimination of EEG signals

  2013cited by this paper
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  2009cited by this paper
• EEG-based motor imagery analysis using weighted wavelet transform features.

  2009cited by this paper
• Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface

  2008cited by this paper
• Breaking the silence: brain-computer interfaces (BCI) for communication and motor control.

  2006cited by this paper
• The use of a masking signal to improve empirical mode decomposition

  2005cited by this paper
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  2004cited by this paper
• Design and implementation of an SVM-based computer classification system for discriminating depressive patients from healthy controls using the P600 component of ERP signals

  2004cited by this paper
• Functional brain imaging based on ERD/ERS.

  2001cited by this paper
• Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters.

  1998cited by this paper
• Mental imagery in the motor context.

  1995cited by this paper

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