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Brain-computer interface system based on steady-state visual evoked potential physiological characteristics

A technology of steady-state visual induction and brain-computer interface, which is applied in the fields of electrical digital data processing, input/output process of data processing, computer components, etc. problems, to achieve the effect of improving the classification accuracy and improving the analysis ability

Active Publication Date: 2018-04-24
SOUTHEAST UNIV
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Problems solved by technology

[0005] The application of CCA has greatly improved the classification effect of SSVEP-type BCI, but because the existing SSVEP-type BCI system does not fully consider the physiological characteristics of SSVEP signals, the physiological characteristics are not used as constraints in the analysis process. Optimization, which affects the classification effect of the BCI system

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  • Brain-computer interface system based on steady-state visual evoked potential physiological characteristics
  • Brain-computer interface system based on steady-state visual evoked potential physiological characteristics
  • Brain-computer interface system based on steady-state visual evoked potential physiological characteristics

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Embodiment Construction

[0027] The technical solution of the invention will be described in detail below in conjunction with the accompanying drawings.

[0028] Aiming at the defect that the existing SSVEP-type BCI system does not fully consider the physiological characteristics of SSVEP signals, the present invention proposes a brain-computer interface that analyzes the correlation between SSVEP signals and frequency reference signals under the constraints of the steady-state visual evoked potential spectrum distribution characteristics system.

[0029] The brain-computer interface system based on the physiological characteristics of steady-state visual evoked potential involved in this application is as follows: figure 1 As shown, it includes: a delayed response module, a CCA module, a typical correlation coefficient selection module, and an output module. The delayed response module is used to delay processing the collected steady-state visual evoked potential signal, and the CCA module is used t...

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Abstract

The invention discloses a brain-computer interface system based on steady-state visual evoked potential physiological characteristics, and belongs to the cross technical field of cognitive neural science, information processing and automatic control. The brain-computer interface system comprises a time delay reaction module, a CCA module, a typical correlation coefficient selection module and an output module. A delay reaction of SSVEP is modeled, a characteristic frequency point capable of reflecting the frequency spectrum energy change is selected as a frequency reference signal of SSVEP stimulation, all components of the frequency reference signal are linearly combined to obtain a spectral energy distribution model, and an analysis result of a CCA is optimized under the constraint of the ratio of the components of the frequency reference signal. The quality of SSVEP signals can be improved, the characteristics can be effectively extracted, the analysis capability of the CCA is improved, and finally the classification accuracy of a BCI system is improved.

Description

technical field [0001] The invention discloses a brain-computer interface system based on the physiological characteristics of steady-state visual evoked potentials, in particular to a brain-computer interface system based on improved correlation analysis, which belongs to the intersecting technology of neurocognitive science, information processing and automatic control field. Background technique [0002] Brain-Computer Interface (BCI) is a control method established between the human brain and the external environment. The BCI system can realize the function of controlling external electromechanical equipment through brain consciousness. Effective feature extraction and classification of brain signals is a key technology to improve the performance indicators of BCI systems. Considering the portability and economy of the equipment, the current BCI system mainly uses electroencephalography (Electroencephalography, EEG) signals. [0003] The non-invasive BCI system can be...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01G06K9/00
CPCG06F3/015G06F2218/08G06F2218/12
Inventor 葛盛刘慧孙高鹏
Owner SOUTHEAST UNIV
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