基于虚拟仪器的脑机接口设计与实现

S. Cui, Xiong Su, Genghuang Yang, Li Zhao
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引用次数: 0

摘要

提出了一种基于视觉诱发电位(VEP) P300的在线脑机接口(BCI)。将该方法应用于多自由度机械臂的控制。该BCI系统包括视觉刺激、信号采集、数据处理、通信和机械手运动控制五大模块。基于LabVIEW平台和虚拟仪器技术,设计了仿真程序和实验方案。自主设计开发了具有六方向自由移动和抓取、卸料双向操作能力的机械手。在实验中,被试在CRT/LCD显示器上选择正确的古怪球,并注视它,这些古怪球有8个方块,分别是向前、向后、向上、向下、向左、向右、抓住和释放。对脑电图(EEG)进行采样,提取P300特征。采用峰值提取、相关分析和小波变换等算法对脑电信号进行分析。在比较各算法结果的基础上,选择小波变换提取脑电信号特征。机械手的移动或操作由受试者的脑电图通过有线或无线通信控制。实验表明,实验对象经过少量训练就能控制机械手。本文还对今后的研究提出了改进意见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and implementation of a virtual instrumentation based brain-computer interface
The paper presents an on-line brain-computer interface (BCI) based on visual evoked potential (VEP) P300. The BCI is applied to control a multi-DOF manipulator. This BCI system includes five modules which are visual stimulator, signal acquisition, data processing, communication and motion control of manipulator. Stimulation program and experimental scheme are designed based on LabVIEW platform and virtual instrument technology. The manipulator with the ability of six-direction-free moving and two-direction operation including grasping and relieving is self-designed and developed. In the experiment, the subject chooses the right oddball on a CRT/LCD displayer with eight blocks, those are forward, backward, up, down, left, right, grasp and release, and gazes at it. The electroencephalography (EEG) is sampled to extract the P300 characteristic. The algorithms of peak extraction, correlation analysis and wavelet transform are used to analyse EEG. Based on the comparing of the result of the algorithms, wavelet transform is select to extract the feature of EEG. The manipulator is controlled to move or operate by the subject's EEG with wire or wireless communication. The experiments show that the subject with little training can control the manipulator. The improvement for the future research is also available in the paper.
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