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High arousal EEG intent discrimination method based on complex object control

A technology of complex objects and arousal, applied in the field of physiological signal processing and intent discrimination, can solve the problems of difficulty in satisfying neurorehabilitation, low accuracy of EEG intent recognition, low complexity, etc., to increase experimental immersion and increase separability Sexuality and reliability, the effect of reducing fatigue

Active Publication Date: 2021-05-18
YANSHAN UNIV
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Problems solved by technology

Therefore, in this case, the accuracy of intention recognition of the collected EEG will be relatively low, and it is difficult to meet the needs of neurorehabilitation.
In addition, this low-complexity non-energy-constrained system is difficult to match with the scenes in daily life. However, neurorehabilitation research needs to be based on scenes that are more in line with daily life.

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  • High arousal EEG intent discrimination method based on complex object control
  • High arousal EEG intent discrimination method based on complex object control
  • High arousal EEG intent discrimination method based on complex object control

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Embodiment Construction

[0044] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0045] Such as figure 1 , the implementation of the method of the present invention mainly includes four steps: (1) designing a new paradigm applied to brain-computer interface experiments - controlling complex and constrained objects; (2) building an EEG signal acquisition device to obtain multi-channel motor imagery EEG (3) Use the co-space pattern algorithm to extract and optimize the features of the obtained EEG signals; (4) EEG signal identification and system evaluation, and use the Fisher ratio classification to obtain the EEG signal features The algorithm constructs the best classifier model, obtains the best classifier to classify new EEG features, analyzes the classification accuracy, and draws conclusions by comparing with other methods.

[0046] figure 1 It is a flow chart of the high-arousal EEG intention analysis method based on complex object control in...

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Abstract

The present invention provides a high-arousal EEG intention analysis method based on complex object control, which mainly includes: (1) designing a new paradigm for controlling complex and constrained objects applied to brain-computer interface experiments; (2) acquiring Multi-channel motor imagery EEG signal sample data, and preprocess the signal; (3) use the co-space pattern algorithm to extract and optimize the features of the obtained EEG signal; (4) EEG signal recognition and system evaluation. The method proposed by the present invention combines the corresponding actual manipulation of the presented visual objects to deepen the subject's perception of stimuli, has a higher degree of arousal, and achieves a better classification effect.

Description

technical field [0001] The invention relates to the technical field of physiological signal processing and intention discrimination, in particular to a high-arousal EEG intention discrimination method based on complex object control. Background technique [0002] Brain-computer interface is a new interactive combination of neuroscience and engineering technology, which detects electrical signals generated by brain activities and converts these signals into outputs, and communicates the user's intentions to the outside world. It can be used as a neurorehabilitation tool to improve motor or cognitive performance in patients with neurological disorders such as stroke and quadriplegia. Studies have shown that the imagery of limb movements can alter EEG activity, and different EEG patterns can be obtained under specific motor imagery tasks. EEG signals have been widely used in brain-computer interface systems as an alternative communication channel for people with severe physica...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F3/01
CPCG06F3/015
Inventor 付荣荣韩萌萌王世伟
Owner YANSHAN UNIV