Research Of Embedded Intelligent Wheelchair Control System Based On Single-Channel Bci

Brain computer interface (BCI) is a new human-computer interaction technology and a control path of foreign exchange of information, which is achieved by the establishment of connection between human brain and the outer environment via computers or other electronic equipments. Without relying on peripheral nerve or muscle tissue of the human bodies, BCI technology provides a new way to communicate with the outside world for the physically handicapped.At present, the EEG signal acquisition and processing units of the BCI application systems are realized by multi-channel EEG signal acquisition devices and high performance computers mostly. Although these application systems usually have a good performance, but the disadvantages of huge size, complicated to operate, high cost and high power consumption limit their application. This paper designs and realizes an application system based on single-channel BCI, the embedded intelligent wheelchair control system. The system realizes the motion state control of the wheelchair combined with the embedded microprocessor, used to extract the attention and the eye-blinking signal.The main research works based on previous studies are as follows:1. The dissertation introduces the BCI research status at home and abroad, and proposes a single-channel BCI design scheme based on embedded processor platform after the analysis of the current mainstream EEG signal acquisition and processing schemes in BCI research.2. This article selects attention and eye-blinking signal as the control signal of the embedded intelligent wheelchair control system after the analysis of the EEG signal characteristics. The eye-blinking signal is extracted by using the raw EEG signal.3. This paper designs and realizes an embedded intelligent wheelchair control system based on single-channel BCI. It makes a detailed elaboration about the EEG acquisition module, embedded processor and peripheral circuit module, dc motor driving module, system power supply module, etc. The EEG signal decoding, eye-blinking signal recognition, wheelchair kinetic state control, information display and other software modules, which combines with μC/OS-II and μC/GUI, are also described in detail.4. The hardware and software of the embedded intelligent wheelchair control system based on single-channel BCI are integrated and tested. The test results show that the lowest averaged correct recognition rate of the eye-blinking signal is 87%, the highest is 99%. There is a good linear relationship between attetion and the speed of the wheelchair, and the system has good controllability.