Analysis And Application On Single Channel Eeg Signals

Brain-Computer interface(BCI)is a new man-machine interaction technology,which is gradually becoming a hot topic in social and academic circles via the continuous development of brain science and computer technology in recent years.From the initial application in medical and scientific fields,to the recent commercial and civilian use,and then to the imagination of connecting the virtual world of the metasurverse in the future,BCI technology is rapidly entering people’s daily life.Especially in the recovery and improvement of the limbs of the disabled,and human action assistance and supplement scenes,BCI has a broad application prospect.In this paper,a portable single-channel EEG acquisition device is adopted to develop a mainly EEGartifact-features-using human computer interactive control system on a low-cost,low-power embedded processor platform.Firstly,this paper introduces the EEG signal briefly,including its generating mechanism and characteristics,and discussions of theoretical EEG acquisition knowledge.Finally,the processing method of EEG data from receiving and storing to calculating and converting to theoretical analysis is emphatically described in order to provide basic and reliable EEG data for the following research.Secondly,the characteristics of blinking signals in EEG brainwaves are introduced,and a new algorithm for blinking detection based on sliding window standardization is proposed,which is proved efficiently and reliably after off-line simulation analysis with designed standard experimental paradigm.Simultaneously,the real-time low-delay detection of blinking is realized on the simulation platform,which uses the blinking behavior as the control signal and provides a theoretical basis for the control of external devices in the real-time environment.Thirdly,an online system based on single-channel EEG artifact signal is designed.The work includes constructing system model,improving feature extraction algorithm of double-artifact signal and software design of control system mainly.After Adding the detection of gnash signal into the detection algorithm,developing user interface via App Designer toolkit,and writing/debugging the program code of interface component state control,information display,and related functions,etc,the online real-time BCI control system has realized,which is verified its performance and stability by standard online experiments,and lays a foundation for its deployment on hardware platform.Finally,the hardware design and implementation of embedded EEG artifact control system are completed.Based on the STM32 core processor control,EEG signal acquisition/transmission and peripheral related hardware circuits,the EEG artifact control system was transplanted on the embedded platform,and the brain computer interaction was carried out with a simple EEG calculator displayed on the OLED screen.The input of different length formulas was controlled and the results were calculated by using the characteristics of blink and gnash as well as concentration and relaxation,so as to test the system performance.The test results show that the embedded EEG artifact control and brain computer interaction system has good controllability,real-time performance and effectiveness,which provides a reference for the application research of portable single-guide brain-computer interface technology.