Design And Implementation Of Portable Attention Detection System Based On EEG Signal

The electrical signals generated by brain nerve cells during activities are called EEG signals,and EEG signals have great research value in the fields of clinical medicine and engineering applications.In engineering applications,braincomputer interface technology can establish a bridge between the brain and the computer.Through this technology,the brain's thinking activities can be directly identified and transmitted to the computer.The technology has great theoretical research value.And the practical application prospects have been incorporated into the science and technology development plan by many countries and have become the current research hotspot.In the field of brain-computer interface technology,the use of EEG signals for attention detection is also an important research content.In this paper,the method of using electroencephalogram EEG signal for attention detection is studied,and an attention detection system is designed.In this paper,dry electrodes are used for non-invasive acquisition of EEG signals.The Brain Gear AM EEG chip is used to filter,amplify and convert ADG signals,and then the collected signals are analyzed using Mallat's fast algorithm.The energy of the four rhythms of the EEG signals obtained after the analysis is taken as the eigenvalue,and the obtained feature vectors are classified by the BP neural network.Based on the above,this paper has completed the system design that meets the requirements.The hardware includes signal acquisition and transmission module,signal processing and forwarding module,power module,etc.;the software considers the calculation and portability issues,combines the cloud platform,adopts TCP.The protocol designed the client and server,put the main calculations in the system on the cloud server,and set up the cloud web server for interface interaction.At the same time,the paradigm of attention experiment was designed,and the system was tested by experiment and obtained.Good experimental results.The traditional attention detection method mainly uses the camera and various sensors to recognize the expression and posture of the subject,and it is difficult to accurately quantify the attention level.In this paper,EEG signals are used for attention detection.The test shows that the system can realize real-time acquisition,processing and analysis of EEG signals,which is easier to quantify than traditional methods,with higher accuracy and system volume design.Small and easy to carry.