Bimodal neural signal feature selection method based action intention tasks

A feature selection method and signal feature technology, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as dual-modal feature extraction

Inactive Publication Date: 2018-06-29
FOSHAN UNIVERSITY
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Problems solved by technology

[0004] Most of the existing bimodal feature extraction methods are mainly aimed at language learning, motor imagination, visual and auditory stimulation, and psychological feature extraction, and have not considered bimodal feature extraction based on action intention tasks.

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  • Bimodal neural signal feature selection method based action intention tasks
  • Bimodal neural signal feature selection method based action intention tasks
  • Bimodal neural signal feature selection method based action intention tasks

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Embodiment Construction

[0028] The idea, specific structure and technical effects of the present invention will be clearly and completely described below in conjunction with the embodiments and accompanying drawings, so as to fully understand the purpose, features and effects of the present invention. Apparently, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without making creative efforts all belong to the protection scope of the present invention. In addition, all the connection / connection relationships mentioned in this article do not refer to the direct connection of components, but mean that a better connection structure can be formed by adding or reducing connection accessories according to specific implementation conditions. The various technical features in the invention can be combined interactively on the premise of not conflicting with each oth...

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Abstract

The invention discloses a feature extraction method for a bimodal (electroencephalogram signal / near infrared signal) brain-computer interface system based on action intention tasks. For electroencephalogram signals, frequency domain features, time domain features and spatial pattern features are considered respectively, and based on linear discriminant analysis, the spatial pattern feature with the highest recognition rate is selected. For near infrared signals, variance features, amplitude mean absolute value features and peak value features are considered respectively, and based on linear discriminant analysis, the amplitude mean absolute value feature with the highest recognition rate is selected. The method provides advantageous features for the bimodal brain-computer interface systembased on action intention tasks.

Description

technical field [0001] The invention belongs to the field of brain-computer interfaces (BCI), and specifically relates to selecting effective features of EEG signals and near-infrared signals in action intention tasks. Background technique [0002] The brain is the material basis of all advanced behaviors of human beings. It is composed of a large number of nerve cells, synapses and glial cells. These nerve cells are carrying out spontaneous, rhythmic and comprehensive electrical activities all the time, and the generated electric fields are conducted through volume conductors. Afterwards, a potential distribution is formed on the scalp, and this potential signal with time as the axis is the electroencephalograph (EEG) signal. In the process of cognitive activities in the brain, the oxygen contained in the blood flow of the activated brain area will be greatly increased, and the transmission of oxygen is through the use of hemoglobin in the blood, so the concentration of oxy...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476A61B5/1455
CPCA61B5/14553A61B5/7235A61B5/369
Inventor 王海贤李日成王清赟张友红
Owner FOSHAN UNIVERSITY
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