Parallel noise reduction method and device for electromagnetic field characteristics of vehicle-mounted EEG exogenous interference
An exogenous and electromagnetic field technology, applied in biometric identification, biometric identification mode based on physiological signals, instruments, etc., can solve problems such as inability to process EEG signals, and achieve the effect of improving processing accuracy
Active Publication Date: 2019-07-12
TSINGHUA UNIV
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[0004] Embodiments of the present invention provide a parallel noise reduction method and device for electromagnetic field characteristics of vehicle-mounted EEG exogenous interference, which is used to solve the problem in the prior art that EEG signals cannot be processed under high-intensity external source interference
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[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
[0053] figure 1 is a schematic flow chart of the method of an embodiment of the present invention. Such as figure 1 Shown, the method of this embodiment comprises:
[0054] S11: Acquire the EEG target data set under the condition of stimulation, and obtain the EEG non-target data set under the condition of no stimulation;
[0055] S12: Establi...
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The invention provides a parallel noise reduction method and device for electromagnetic field characteristics of exogenous interference of vehicle-mounted EEG. The method includes: establishing a vector prior table and a lead relationship prior table for the target data set, and verifying the vector prior table and the lead relationship prior table according to the non-target data set to obtain noise reduction prior knowledge; Acquire the EEG signal to be processed, process the EEG signal to be processed in parallel according to the prior knowledge, and obtain the vector inspection probability component, weight inspection probability component and probability inspection probability component of the EEG signal to be processed; according to the vector inspection component, weight The inspection probability component and the probability inspection probability component obtain the processing result of the EEG signal to be processed, and complete the denoising of the EEG signal. The invention reduces the influence of interference sources on EEG under high-intensity external source interference, reduces the influence of interference sources on EEG under multi-band external source electric field interference and magnetic field interference, and improves the processing accuracy of EEG signals.
Description
technical field [0001] The invention relates to the technical field of EEG signal processing, in particular to a parallel noise reduction method and device for electromagnetic field characteristics of exogenous interference of vehicle-mounted EEG. Background technique [0002] As an important electrophysiological indicator of the human body, EEG is of great significance to fields such as medical treatment, scientific research, brain-computer interface research, and aerospace. However, EEG signals are extremely weak and are easily affected by external electromagnetic interference. More and more, electromagnetic interference in the external environment is very complex. Generally, EEG amplifiers need to build a special shielding room when they are in use, and EEG monitoring will not work when they are disturbed when using an electrosurgical knife. These bring great inconvenience to the use of electrophysiological signals and limit these technologies. Applications. [0003] Th...
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IPC IPC(8): G06K9/00G06K9/40A61B5/0476
CPCG16H50/30A61B5/7203A61B5/369G06V40/10G06V40/15G06V10/30
Inventor 张罡杨建高小榕刘进
Owner TSINGHUA UNIV