Emotional electroencephalogram signal recognition method based on EMD domain multi-dimensional information

A technology of multi-dimensional information and EEG signals, applied in medical science, psychological devices, sensors, etc., to achieve excellent performance and improve classification accuracy

Active Publication Date: 2017-11-21
THE PLA INFORMATION ENG UNIV
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But which features are most effective for emotion recognition in the EMD domain? Which IMF co

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  • Emotional electroencephalogram signal recognition method based on EMD domain multi-dimensional information
  • Emotional electroencephalogram signal recognition method based on EMD domain multi-dimensional information
  • Emotional electroencephalogram signal recognition method based on EMD domain multi-dimensional information

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[0050] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them.

[0051] This embodiment is carried out under the simulation environment of Matlab2014b, using the EEG data of the DEAP emotion database. The DEAP database uses EEG equipment to record the EEG signals of 32 subjects while watching music videos with different emotional stimuli. The electrode distribution of the EEG conforms to the international 10-20 system. In this embodiment, the preprocessed EEG signal is used, and the sampling frequency is 128 Hz, the oculoelectric artifact is removed, and the EEG signal is subjected to 4-45 Hz band-pass filtering.

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Abstract

The invention relates to the technical field of electroencephalogram signal processing, in particular to an emotional electroencephalogram signal recognition method based on EMD domain multi-dimensional information. The method includes the steps that electroencephalogram signals are adaptively decomposed into intrinsic mode functions (IMF) with different oscillation frequencies through EMD; then, the waveform difference, phase difference and normalized energy of the IMFs are extracted; feature vectors are formed by the extracted multi-dimensional information to serve as the representation of different emotional electroencephalogram signals; the emotional electroencephalogram signals are classified and recognized through a KNN classifier and an SVM classier. Thus, the classification accuracy is greatly improved.

Description

technical field [0001] The invention relates to the technical field of EEG signal processing, in particular to an emotional EEG signal recognition method based on EMD domain multi-dimensional information. Background technique [0002] Emotions play an important role in our daily life and work, real-time evaluation and regulation of emotions can better improve people's quality of life. For example, in the communication of human-computer interaction, emotion recognition will make the interaction process more harmonious and natural. Another example, during the treatment of patients, especially those with expression problems, the real emotional state of the patient will help doctors provide more accurate medical services. In recent years, emotion recognition based on EEG signals has received extensive attention. Furthermore, it is a very important factor in brain-computer interface (BCI) systems, which can effectively improve communication between humans and computers. [000...

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Application Information

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IPC IPC(8): A61B5/0476A61B5/16A61B5/04A61B5/00
CPCA61B5/165A61B5/7264A61B5/316A61B5/369
Inventor 闫镔庄宁曾颖张弛童莉
Owner THE PLA INFORMATION ENG UNIV
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