Channel selection method based on fractal dimension
A fractal dimension and channel selection technology, applied in the field of brain-computer interface technology and information processing, can solve the problems of high computational complexity and dependence on early feature engineering, and achieve the effect of simplifying EEG signal processing and improving convenience
Active Publication Date: 2020-02-07
XIAN UNIV OF POSTS & TELECOMM
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[0008] In view of this, the present invention provides a channel selection method based on fractal dimension to overcome the problems of high computational complexity, reliance on early feature engineering, and reliance on existing neurophysiological cognition existing in the prior art
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[0038] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0039] The present invention proposes a channel selection method based on fractal dimension, such as figure 1 As shown, this method includes three key steps: extraction of brain power components, quantitative analysis of brain power components, and back projection of brain power components. The specific steps are as follows:
[0040] Step 1, using the DEAP public emotion data set as the EEG signal to be analyzed;
[0041] Step 2, extracting brain power components: obtaining the same number of brain power components as the number of originally collected EEG signal channels through independent compo...
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The invention relates to the technical field of brain-computer interface technologies and information processing, in particular to a channel selection method based on fractal dimension. The problems of high calculation complexity, dependence on early-stage feature engineering and dependence on existing neurophysiology cognition in the prior art are solved. The method comprises the following steps:(1) taking a DEAP common emotion data set as a to-be-analyzed electroencephalogram signal; (2) a brain power supply component extraction stage: performing source component extraction on the multi-channel electroencephalogram signals through an independent component analysis method; (3) a brain power supply component quantitative analysis stage: converting the plurality of brain power supply components extracted in the step (2) into a time-frequency image through Wigner distribution, and performing quantitative evaluation on the information content contained in the time-frequency image throughfractal dimension; and (4) a brain power supply component back projection stage: sorting numerical values obtained by fractal dimension calculation of each brain power supply component in the step (3) from large to small in sequence, and realizing back projection through an equivalent dipole analysis method.
Description
technical field [0001] The invention relates to the fields of brain-computer interface technology and information processing technology, in particular to a channel selection method based on fractal dimension. Background technique [0002] Brain-Computer Interface (BCI) technology is a system that realizes mutual control and communication between the human brain and computers or other electronic devices by using bioelectrical signals detected inside the brain, on the surface of the cortex, and on the scalp, allowing users to communicate without peripheral nerves. Communicate effectively with the participation of systems and musculature. EEG signals are widely used in brain-computer interface technology due to their non-invasive, convenient acquisition, relatively cheap, and high temporal resolution. Compared with emotion recognition methods based on facial expressions, body postures, and speech, emotion recognition based on EEG signals has gradually become a research hotspot...
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Login to View More IPC IPC(8): G06K9/00G06F3/01
CPCG06F3/015G06F2218/12
Inventor 贺炎冯璁张荣王文浪王忠民
Owner XIAN UNIV OF POSTS & TELECOMM