Research And Design Of Home Appliances Integrated Control System Based On Brain-computer Interface

Brain-computer interface (BCI) is a technology that use the brain bioelectrical signalsto communication with a computer or other equipments. The identification and classificationof EEG is the significant problem of the brain computer interface. In this paper, we mainfocus on the event-related potentials of P300signal. The research of this paper includes thephysiological mechanism, platform design, algorithm design, online experiments and so on.The experiments results show that our system can successfully control electric light, and TVand communicate in word. Furthermore this system can help Nerve dysfunction patients (suchas paralysis patients) improve their capabilities to care for themselves. This paper is organizedas follows:First, we present the P300analysis method, including the EEG signal collection, EEGpreprocessing, P300feature extraction and the classifier design. We illustrate the value of thepractical P300signal according to the theory, which can provide a theoretical basis for theintegrated control of the P300BCI appliances.Second, we build a platform for the P300BCI appliance control system. We design a twolayers control mode, successfully choose the control object and operate the control object,Platform building work is a key part in this paper, And it is also a key part of the wholeexperiment. In this section, including how to induce production of the P300signal, how toinduce synchronization of signals and brain waves, how to identify the P300brain wavesignal, finally, there is how to identify the results converted into control commands. Brainwaves are very weak, and P300requirements are very strict time control, so the BCI systemhardware and software requirements are very strict. We must pay special attention to somedetails, such as the synchronization signal generation and flashing sequence. We will have abetter understanding of the P300signal through the setting up platform and platformparameter settings.Third, the offline data analysis and online testing of the P300brain-computer interfaceappliance integrated control system. In this part we will test the feasibility, stability andreliability of the entire system. And to improve system performance by off-line test. The mainapproach is to analyze the accuracy of the offline data in the case of different number of flashes, and set a reasonable online test parameter based on the results of the analysisparameters. Finally, the online effect will reflect the system performance.This BCI system is mainly used for motor function in patients with impaired. Presently,the research on the control of brain-computer interface system is mainly focus on a singleobject (such as light, TV, etc.). This paper utilizes stratified control technology to achieve theintegrated control system of home appliances, and assisted in their daily lives more easily.