Method for extracting features of motion imagination electroencephalogram signal based on Multi-bands FDBN

An EEG signal and feature extraction technology, applied in the intersection of brain science and computer science, and in the field of motor imagery EEG signal processing, can solve problems that have not reached the level of practical application, achieve small variance, good robustness, and improve The effect of stability and average recognition rate

Inactive Publication Date: 2017-08-25
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0004] At present, the research on BCI has achieved certain results, but it is far from reaching the level of practical application.

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  • Method for extracting features of motion imagination electroencephalogram signal based on Multi-bands FDBN
  • Method for extracting features of motion imagination electroencephalogram signal based on Multi-bands FDBN
  • Method for extracting features of motion imagination electroencephalogram signal based on Multi-bands FDBN

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Embodiment Construction

[0036] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.

[0037] The technical scheme that the present invention solves the problems of the technologies described above is:

[0038] The technical solution provided by the invention is a feature extraction method of motor imagery EEG signals based on Multi-bands FDBN. The flow chart of the present invention is as figure 2 As shown, the specific steps of the method are:

[0039] Step 1: Preprocessing; the EEG signals collected by the signal acquisition equipment are passed through a filter bank composed of multiple bandpass filters according to the individual differences of the signal frequency band information, and then the signals passing through the filter bank are transformed using FFT ,, and finally use the...

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Abstract

The invention requests to protect a method for extracting the features of a motion imagination electroencephalogram (EEG) signal based on Multi-bands FDBN (Fractional Deep Belief Network). The method comprises the following steps: first, dividing an original EEG signal into multiple bands through a band-pass filter; then, converting the time-domain signal into a frequency-domain signal for each band through FFT, and normalizing frequency-domain data in a global min-max way; and finally, inputting the frequency-domain data of each band to a DBN for training and identification, and fusing the results of multiple softmax classifiers by means of weighted calculation. The problem that different frequency band information functions differently is solved from the design. The robustness of the algorithm is further ensured through multiple classifiers. The classification accuracy of EEG signals can be improved greatly.

Description

technical field [0001] The invention belongs to the field of motor imagery EEG signal processing, in particular to a method for feature extraction of motor imagery EEG signals based on Multi-bands FDBN, which is an interdisciplinary field of brain science and computer science. Background technique [0002] The brain is an extremely fine and complex organizational structure. The completion of a set of actions usually generates stimulating potentials through the corresponding areas of the brain. These potentials are transmitted to different parts through neuron cells, and then communicate with the outside world through muscle tissue or the peripheral nervous system. build connection. However, there are countless situations in the world where people lose their ability to exercise due to diseases or accidents every year. It has been reported that more than 2 million people suffer from atrophic lateral sclerosis and spinal cord injuries in the United States. Similar diseases Str...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06F2218/08G06F2218/12
Inventor 蔡军胡洋揆曹慧英尹春林陈永强唐贤伦郭鹏张毅
Owner CHONGQING UNIV OF POSTS & TELECOMM
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