| The Brain-Computer Interface(BCI)system without relying on the normal output path of the brain enables real-time communication and direct interaction between the brain and a computer or other electronic device.With the advancement of technologies such as computer and signal processing,the BCI system has achieved many results and has also significantly improved in terms of system performance.However,most of the BCI systems currently under study are not open type,and some of the internal processing methods of the system cannot be modified separately.The degree of coupling of the system is relatively high,and the independence is poor.It is not convenient for requirement modification.Based on this situation,this thesis designs an open BCI application software platform to solve coupling problems and compatibility problems well,and to facilitate the modification of functional requirements.In this platform,a variety of BCI systems can be constructed.This paper builds BCI based on motioninduced visual evoked potentials and steady-state visual evoked potentials.The application software platform of this paper is mainly composed of hardware part and software part.The hardware part is portable two-channel EEG acquisition system.The software part is the combination of Simulink modular construction and Qt-based interface design.Bluetooth is used for communication between the hardware part and the software part,and the software internally uses the TCP network for communication,so that the system has good device compatibility.The hardware part includes the design of EEG signal acquisition circuit and acquisition software.The software part is mainly designed and applied based on data transmission,signal preprocessing,feature extraction and pattern classification modules in Simulink,as well as stimulation and feedback interface,signal acquisition and transmission through Qt interface design.In order to verify the performance of this platform,verification experiments were designed for the hardware part and the software part.The experimental results show that all the functions of this platform can basically meet the needs of the BCI system.Finally,based on this platform,a BCI system based on mVEP and SSVEP was built and tested,both systems were basically able to meet the needs of experimental applications. |
