一种运动想象脑机接口训练系统的设计

目的 为提高运动想象的脑机接口训练速度和效率,本文设计了一种训练系统.系统功能主要包括参数设置、EEG采集、特征提取、分类及其结果反馈、分类器模型建立.方法 在训练系统设计中,首先使用VC＋＋编写的脑电信号采集软件获取脑电信号,而后通过TCP/IP实现与MATLAB之间的数据传输,在MATLAB中实现特征提取与分类识别,并将识别结果实时反馈给受试者,使受试者能够及时调整自身状态,并选择合适的反馈方式,从而在较短时间内生成有效的分类器模型.结果 该系统具有接口方便、功能强大、界面友好的特点,通过建立的在线系统对训练系统进行了初步检验.结论 该系统可使使用者进行方便有效的训练,进而缩短训练时间并提高脑机接口系统的识别正确率,为脑机接口应用系统的实现奠定了基础.

Training system for brain computer interface based on motor imagery

Objective To improve the training efficiency of brain computer interface （BCI）training based on motor imagery, the paper designs a training system including parameter setting, electroencephalography （EEG） acquisition,feature extraction, classification, feedback of results and the foundation of classifier model. Methods Firstly,the training system acquires the EEG signals of motor imagery by EEG acquisition software, and then transmits data to MATLAB with TCP/IP protocol. So the feature extraction and classification are realized in the MATLAB. After that,the training system feedbacks the recognition results with the progress bar at the same time, and allows subjects to adjust their status in the training. Finally the system generates an effective classification model by choosing a proper feedback mode in a short time. Results The characteristics of the system are convenient intervention, powerful function and friendly interface. A BCI online system is established to test the training system and an effective classification model can be completed in a relatively short period of time. Conclusions The training system can improve the recognition rate and shorten the training time for BCI application systems,which lays the foundations for BCI application systems.