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Upper limb movement imagination pattern recognition based on multi-modal signals

A motion imagery and pattern recognition technology, applied in the fields of medical science, sensors, use of spectral diagnosis, etc., can solve the problems of improving the recognition rate, easy to be interfered, non-stationary, etc., and achieve the effect of high classification and recognition rate

Inactive Publication Date: 2019-01-11
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

However, the single use of EEG signal recognition still has the following problems: EEG signals cannot reflect the information in the spatial domain well, which is not conducive to improving the recognition rate; the amplitude of EEG signals is relatively weak, with significant non-stationarity and nonlinearity, which is easy to being disturbed etc.

Method used

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  • Upper limb movement imagination pattern recognition based on multi-modal signals
  • Upper limb movement imagination pattern recognition based on multi-modal signals
  • Upper limb movement imagination pattern recognition based on multi-modal signals

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Embodiment Construction

[0024] The present invention will be further described below in conjunction with accompanying drawing.

[0025] figure 1 It is a flowchart of the present invention. figure 2 It is a flowchart of a single experimental action for collecting multi-modal signals. Specifically, the subject performs related actions in a comfortable and relaxed environment according to the relevant prompts displayed on the computer. The action time is 5s. After each action is completed, the subject The patient rested for 10 seconds according to the prompts to restore the blood oxygen content of the brain, and so on. 5 seconds before the start of the experiment, the screen displayed the precautions for the experiment, and the subjects looked at the screen and kept relaxed; at the 5th second, the prompt text ended, and the video and text prompts of left and right hand movements were randomly displayed on the screen; after the clenched fist prompt video ended, the screen The relaxation text prompt is...

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Abstract

The invention relates to an upper limb movement imagination pattern recognition based on multi-modal signals. At first, the movement imagination pattern recognition based on multi-modal signals calculates the original near infrared spectrum signal to obtain the oxygenated hemoglobin content in the brain, and extract the CSP characteristic from the oxygenated hemoglobin content value; secondly, thesample entropy is extracted from the EEG signal; then, the obtained multimodal features are normalized and serially fused; and finally, the support vector machine model is used to classify the fusedmulti-modal features. The movement imagination pattern recognition based on multi-modal signals has the advantages of maintaining high spatial resolution of the electroencephalogram signal, and supplementing the characteristics of high temporal resolution of the near-infrared spectrum signal at the same time, so that the recognition rate of the upper limb movement imagination mode is improved.

Description

technical field [0001] The invention relates to a brain-computer interface technology for identifying upper limb motor imagery patterns, in particular to a multimodal upper limb motor imagery pattern recognition method based on electroencephalogram signals and synchronous near-infrared spectrum signals. Background technique [0002] Brain-computer interface technology plays a great role in rehabilitation medicine and artificial intelligence control. This technology can enable some stroke and hemiplegia patients with motor nerve damage to complete various behaviors with the help of external devices and overcome functional obstacles of patients. [0003] Commonly used brain-computer interface technologies are often based on the analysis of EEG signals. The acquisition of EEG signals is sensitive and non-invasive, and the signals have high time resolution, which can reflect the changes of brain regions in the process of thinking activities to a certain extent. Based on this ch...

Claims

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Application Information

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IPC IPC(8): A61B5/0476A61B5/00
CPCA61B5/0075A61B5/7264A61B5/369
Inventor 马玉良缪楚泱刘卫星孟明张启忠
Owner HANGZHOU DIANZI UNIV
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