基于TI OMP3530的SSVEP脑机接口系统设计
he SSVEP BCI System Design Based On TI OMP3530
本文设计了一种基于稳态视觉诱发电位（Steady-state visually evoked potentials, SSVEP）的脑-机接口(Brain-Computer Interface, BCI)系统，系统主要包括五部分：视觉刺激模块、脑电采集模块、桥接转发模块、数据处理模块、控制模块。系统利用白色LED视觉刺激器产生特定频率的视觉刺激，当人眼受到刺激后，在大脑皮层产生与之相关的诱发电位信号，通过EPOC设备进行诱发电位信号采集、放大，然后通过桥接转发模块将信号发送出去，并基于OMAP3530开发平台，利用典型相关分析算法(Canonical Correlation Analysis, CCA)对诱发信号进行特征提取与分类，产生控制命令控制无线小车的方向。本系统利用滑动窗口机制，通过受试者平均测试可将系统识别准确率控制在90%以上，且人机交互实时速率控制在2s范围内，完全满足实际需求。
his Paper designed the Brain-Computer Interface System that based on Steady-state visually evoked potentials, the system mainly includes five parts: the visual stimulus module, the EEG signal acquisition module, the bridge forwarding module, the data processing module, the control module. The LED visual stimulator emitted a specific frequency of stimulation to initiate the relative evoked potentials in cerebral cortex, and then collected the potentials through the EPOC device. The EPOC sent out the signals through bridge fordwarding module. When the platform of OMAP3530 received the signal, the feature extraction and classfication were performed by the algorithm of Canonical Correlation Analysis and finally the control command was sent to the wireless car. The system can get accuracy of 90% with the sliding windows, it can meet the actual needs completely.
吴强、刘琚、董贤光
电子技术应用
脑-机接口稳态视觉诱发电位(SSVEP)典型相关分析算法(CCA)I OMAP3530滑动窗口机制
Brain-Computer Interface(BCI)Steady-state visually evoked potential(SSVEP)Canonical Correlation Analysis(CCA)TI OMAP3530Sliding windows
吴强,刘琚,董贤光.基于TI OMP3530的SSVEP脑机接口系统设计[EB/OL].(2017-01-05)[2025-05-16].http://www.paper.edu.cn/releasepaper/content/201701-66.点此复制
评论