Design method of human-computer interaction system for motor imagery training based on eye electricity and brain electricity
A technology of motor imagination and human-computer interaction, applied in the directions of user/computer interaction input/output, calculation, mechanical mode conversion, etc., can solve problems such as misleading EEG signal recognition
Active Publication Date: 2019-03-01
西安慧脑智能科技有限公司
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However, human eyes sometimes move unconsciously. At this time, the brain does not perform motor imagination. The electrooculogram signal at this time cannot assist in the recognition of EEG signals, but will mislead the recognition of EEG signals.
[0005] The method of fusing the effective information contained in the EEG signal and the EEG signal can eliminate the misleading caused by the unconscious EEG signal, improve the recognition accuracy of the EEG signal, and conduct pattern recognition on the EEG signal of different individuals in a timely and accurate manner. At present, the construction method of this type of algorithm still needs further research and exploration.
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[0049] A human-computer interaction system design scheme for upper limb rehabilitation based on ophthalmography and EEG proposed by the present invention is to place the scalp electrification electrodes in the electroencephalogram pickup sensor into the standard 10-20 lead system of the International Electroencephalography Society The determined position corresponding to the top of the head and the sensorimotor area of the brain is C 3 、C Z and C 4 position, to collect three channels of EEG signals corresponding to the user; at the same time, place the pick-up electrode of the electro-ocular pick-up sensor on the outer corner of the left eye, the reference electrode on the earlobe of the left ear, and the GND electrode on the earlobe of the right ear. The three-channel EEG signal and the horizontal oculoelectric signal collected by the sensor are intercepted, denoised and other preprocessing links are applied to identify the user's motor imagery intention by applying the me...
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The invention discloses a design method of a human-computer interaction system for motor imagery training based on eye electricity and brain electricity. The invention provides a method for patients with motor dysfunction, which can identify and give feedback on the motor imagery state of their brains in a timely and effective manner. . This method is to use the signal acquisition equipment to obtain the change data of EEG and EEG signals when the human body completes specific upper limb movements during the brain's upper limb motor imagination process, and store them in the individualized database as the information source, and then separately Feature extraction is performed on electrical signals and electrooculogram signals, and the two types of features are fused as new motor imagery features using the criteria based on the information fusion scheme, and the new motor imagery features are identified, and then the motor imagery state when the person completes the specified action is analyzed. to identify.
Description
technical field [0001] The invention belongs to the field of bioelectrical signal processing and relates to the current rehabilitation medical treatment. When the human body completes a specific action, the system fuses the electroencephalogram signal and the electrooculogram signal to perform pattern recognition, and at the same time feeds back the recognition result to the user to assist the user to complete the upper limb The motor imagery training of the invention specifically relates to a design method of a human-computer interaction system for motor imagery training based on eye electricity and brain electricity. Background technique [0002] The human-computer interaction system records the EEG signal of the user's motor imagery by the acquisition system, and then transmits it to the signal processing system to obtain the signal feature vector and perform pattern recognition. Finally, the pattern recognition result is sent to the neurofeedback device. The neurofeedback...
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IPC IPC(8): A61B5/0476A61B5/0496G06F3/01G06K9/62
CPCG06F3/015A61B5/7253A61B5/316A61B5/398A61B5/369G06F18/24
Inventor 孙曜王灿锋郭春生
Owner 西安慧脑智能科技有限公司