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Method for capturing signals and extracting characteristics of stand imagination action brain wave

An electroencephalogram signal and signal acquisition technology, which is applied in the fields of biomedical engineering and computer, can solve the problems of slow progress, limited applicability, and difficulty in improving the judgment accuracy of pattern extraction of imaginary action potentials of lower limbs.

Active Publication Date: 2009-01-28
中电云脑(天津)科技有限公司
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AI Technical Summary

Problems solved by technology

But so far, the pattern extraction of lower extremity imaginary action potentials has progressed slowly, and it is difficult to improve the accuracy of judgment
The main reason is that the functional area of ​​the cerebral cortex mapped by the movement of the lower extremities is a relatively narrow area in the parietal sulcus, and the distinction of its spatial structure is already very limited. In addition, the EEG signals extracted by the scalp electrodes are extremely diffuse and inconsistent. Aliasing, very unfavorable for source signal acquisition and identification
This key factor leads to the limited applicability of the feature extraction algorithm applied to the imagery EEG of the upper limbs in the feature extraction of the EEG of the lower limbs.

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  • Method for capturing signals and extracting characteristics of stand imagination action brain wave
  • Method for capturing signals and extracting characteristics of stand imagination action brain wave
  • Method for capturing signals and extracting characteristics of stand imagination action brain wave

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Embodiment Construction

[0011] The present invention proposes a new algorithm for feature extraction of standing-up imaginative action EEG using wavelet envelope independent component analysis (Independent Component Analysis, ICA): first, apply wavelet domain independent component analysis combined with frequency domain ERD / ERS coefficient screening to carry out spatial filtering The new method realizes the brain power signal of the key lead when standing up and imagining; and then analyzes the characteristic information of the ERD / ERS phenomenon caused by standing up and imagining action thinking through the time-frequency Power Spectral Density (PSD) distribution map and power spectral density curve , so as to extract the EEG features with obvious discrimination at the characteristic frequency bands (mu rhythm and beta rhythm) of the characteristic leads. At the same time, the different effects of this method and the feature extraction of standing up imagination action EEG based on traditional indep...

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Abstract

The invention belongs to the field of biomedical engineering and computer, and relates to a signal collecting and characteristic extraction method used for standing imagining action electroencephalogram. The method of the invention mainly comprises the steps as follows: (1) collecting and pre-processing of standing imagining action electroencephalogram signals; (2) spatial gaining of characteristic small wave package; (3) independent component analysis of small wave package domain; (4) reconstruction of electroencephalogram signals; (5) signal extracting. The method of the invention solves the problem of exact extraction of the electroencephalogram characteristic in standing imagining electroencephalogram action, thus providing powerful supports for correctly recognising the lower limbs motion mode, effectively converting the mode into the control command applied to a lower limbs auxiliary recovery system and realizing the self-standing of the paraplegia patients.

Description

technical field [0001] The invention relates to a method for collecting and feature-extracting electroencephalogram signals, belonging to the fields of biomedical engineering and computers. Background technique [0002] Brain-computer interface (Brain-Computer Interface, BCI) is to establish a direct information exchange and control channel between the human brain and computers or other electronic devices that does not depend on conventional brain output pathways (peripheral nerves and muscle tissue). A new human-computer interaction system. The earliest EEG signals applied to the brain-computer interface system are mainly spontaneous EEG signals, such as alpha (α) waves in EEG. However, this type of EEG signal mode is single, and it is impossible to truly achieve "consciousness control action", which seriously restricts the development of brain-computer interface systems. In recent years, scholars from various countries have gradually carried out research on EEG signals u...

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Application Information

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IPC IPC(8): A61B5/0476
Inventor 万柏坤周仲兴明东綦宏志程龙龙
Owner 中电云脑(天津)科技有限公司
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