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Motor imagery analysis method and system based on EEG brain-computer interface
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A technology of motor imagery and brain-computer interface, applied in the field of EEG analysis, can solve problems such as lack of precision solutions, and achieve the effect of easy modification and upgrade
Pending Publication Date: 2022-04-19
SHANDONG NORMAL UNIV
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(2) The performance of the SMR-BCI is largely dependent on the neurophysiological and psychological state of the user, and many users find the control of SMR activity challenging
[0007] In summary, the existing technology is used for motor imagery analysis problems, and there is still a lack of highly accurate and efficient solutions
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Embodiment 1
[0049] Such as figure 1 As shown, a motor imagery analysis method based on EEG brain-computer interface, including:
[0052] According to the extracted features, feature selection and classification are performed to obtain analysis results;
[0053] Wherein, the feature selection and classification include performing principal component analysis on the EEG data, passing the most discriminative feature among the extracted features to the classifier, and estimating the imagined limb movement of the subject according to the classification result.
[0054] specific,
[0055] Such as figure 1 As shown, the present invention provides a motor imagery analysis method based on an EEG brain-computer interface, which includes five main parts: acquisition of original EEG data, EEG data preprocessing, feature extraction, feature selection and classification.
[0056] S1. Obtai...
Embodiment 2
[0096] A motor imagery analysis system based on EEG brain-computer interface, including:
[0097] The data acquisition module is configured to acquire raw EEG data;
[0098] The feature extraction module is configured to perform feature extraction according to the acquired raw EEG data;
[0099] The analysis module is configured to perform feature selection and classification according to the extracted features, so as to obtain analysis results;
[0100] Wherein, the feature selection and classification include performing principal component analysis on the EEG data, passing the most discriminative feature among the extracted features to the classifier, and estimating the imagined limb movement of the subject according to the classification result.
Embodiment 3
[0102] A computer-readable storage medium, in which a plurality of instructions are stored, and the instructions are suitable for being loaded by a processor of a terminal device and executing the method for analyzing motor imagery based on an EEG brain-computer interface provided in Embodiment 1.
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Abstract
The invention provides a motor imageryanalysis method based on an EEG brain-computer interface. The motor imageryanalysis method comprises the following steps: acquiring electroencephalogram data; performing feature extraction according to the acquired electroencephalogram data; performing feature selection and classification according to the extracted features to obtain an analysis result; wherein the feature extraction comprises the steps of extracting time domain features through autoregression modeling, and extracting frequency domain features through fast Fourier transform. According to the method, original electroencephalogram data are obtained through the EEG brain-computer interface, imaginary limb movement of a subject is estimated through real-time analysis of the data, and the subject is helped to complete the imaginary limb movement through traction of the movement auxiliary equipment. The device is helpful for assisting the limb movement recovery of the brain injury patient.
Description
technical field [0001] The invention relates to the technical field of electroencephalogram analysis, in particular to a method and system for analyzing motor imagery based on an EEG brain-computer interface. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] In recent years, people have used brain-computer interfaces (BCIs) to realize the conversion of brain signals and computer data, which means that computers can be controlled consciously by monitoring the signal activity of the brain. [0004] Compared with other methods such as functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG), EEG signals are non-invasive, have high temporal resolution, are portable, and have relatively low Due to its cost and other advantages, EEG is widely used to record brain signals in BCI systems. EEG-based BCI can be divided into two ...
Claims
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