结合表面肌电与稳态视觉诱发电位的混合脑机接口关键技术研究

脑-机接口技术旨在大脑与外部环境之间建立一种全新的不依赖于外周神经和肌肉的交流与控制通道。基于稳态视觉诱发电位的脑-机接口是目前信息传输率最高的无创脑 机接口范式，但是仍低于传统的交互方式。提出一种结合表面肌电与稳态视觉诱发电位的混合脑 机接口，以进一步提高系统的信息传输率。通过不同频率的高频稳态视觉诱发电位结合sEMG编码，实现二者混合脑 机接口系统。利用典型相关分析方法对SSVEP信号进行频率识别，sEMG的检测则采用频域分析方法。来自8名健康受试者的离线结果表明该系统能够获得8428% 的平均准确率，平均信息传输率为7263 bits/min。这些结果为结合表面肌电与稳态视觉诱发电位的混合脑 机接口研究奠定了基础。     

基于SSVEP的脑-机接口自动车系统研究

阐述了视觉诱发电位用于脑-机接口的原理,系统采用单片机设计视觉刺激器,同时在LABVIEW平台上,利用希尔伯特黄变换实时提取诱发电位向量,产生脑机接口控制信号,并用于自动车控制系统,从而控制小车的前后左右运动.通过大量实验验证,设计的基于稳态视觉诱发电位的脑-机接口自动车控制系统,发送控制命令正确率高于83％,发送一个...     

异步BCI的大脑工作和空闲状态的辨识方法研究

基于事件相关电位的脑-机接口系统难以检测大脑的空闲状态,限制了被试在任意时间输出指令的自由。利用欧德堡范式同时诱发N200电位、P300电位和瞬态视觉诱发电位。根据瞬态视觉诱发电位的频域特征区分大脑的工作状态和空闲状态;在工作状态下利用N200和P300电位的时域特征识别被试的控制意图,从而构建异步的脑-机接口系统。通过对7名健康被试进行发送指令与观看视频反馈两种状态的实验,实现大脑的工作状态和空闲状态之间的切换。该方法识别大脑状态或者意图的准确率为98.21%,与基于事件相关电位识别空闲状态的方法相比提高了50.89%。     

DSP在基于想象动作电位的脑-机接口中的应用

应用数字信号处理器设计了一个基于想象动作电位的脑-机接口系统,通过模拟滤波与数字信号器处理相结合的方法,实现了对想象动作电位信息的有效采集和处理.系统在硬件上设计了脑电信号放大器,DSP开发板;对脑电信号放大、AD转换后,通过分类特征提取处理后,完成动作识别与控制命令的输出.将数字信号处理器应用在脑-机接口中,利用数字信号处理器优异的处理能力和丰富的外设资源,实现了一个嵌入式、微型化的脑-机接口构建,实现了脑-机接口实时处理与微型化.     

基于Hilbert Huang变换的SSVEP相位提取

稳态视觉诱发电位(steady-state visual evoked potential,SSVEP)被广泛应用于脑-机接口和大脑的认知研究,相位信息是其重要的特征指标之一.针对快速傅里叶变换在SSVEP相位提取中受不确定性原理约束的特点,提出了一种基于Hilbert-Huang变换的SSVEP相位提取方法.该方法通过经验模态分解将脑电信号分解为一系列固有模态函数(intrinsic mode functions,IMF),并通过分析各模态函数瞬时频率的均值判断该IMF分量是否属于噪声.若为噪声则将其从原始信号中滤除,再对滤波后的各IMF分量进行Hilbert变换,并与基准信号做运算即可求得SSVEP相位.实验结果表明,与快速傅里叶法相比该方法可在去除噪声分量的同时提取SSVEP的相位信息,且具有较高的准确率、精度和自适应性.     

α波和运动想象的混合范式脑-机接口系统

提出将α波和运动想象2种范式以串行的方式相结合控制的脑-机接口系统,该系统利用α波的阻断现象控制状态选择,选择成功后发出提示音,被试听到提示音后,通过左右手运动想象来完成多个任务。通过这样的混合范式有效的实现了较少种类的脑电信号对外部设备的多任务控制。实验结果表明,5名被试都能顺利完成外部设备的多任务控制,平均正确率为77%,最高正确率可达90%。本系统实现了混合范式下的脑电信号对外部设备的多任务控制,为进一步开发复杂的混合范式的脑-机接口系统奠定基础。     

听觉刺激对稳态视觉诱发电位影响研究

基于稳态视觉诱发电位(steady state visual evoked potential,SSVEP)和听觉脑机接口技术目前已成为研究重点.未来的挑战是研究基于视觉和听觉联合统一系统框架的脑机接口技术.多感觉在不同脑区间存在的跨膜整合以及视听双刺激的交互作用,给该技术研究带来较大困难,故研究听觉刺激对枕区SSVEP影响很有意义.在闪光刺激频率为12 Hz,占空比分别为5％、20％、30％、40％、50％、60％、70％、80％、95％条件下,分别加入500、1 000、1 500 Hz的正弦纯音、响度为50 dB的听觉刺激,研究听觉对SSVEP的变化规律.结果表明,对同一受试者,视听双刺激条件下SSVEP随占空比变化依然呈现“窗口”效应,听觉刺激对SSVEP影响起增强或抑制作用.此外听觉刺激对SSVEP影响出现的占空比“窗口”的位置、数量以及对SSVEP增强或抑制作用的程度也因人而已.结果为更好研究视听相互作用机理及其在脑机接口技术应用提供有意义的实验依据.     

基于LabVIEW和OPC的异步电机测试系统

为提高异步电机测试的效率,将计算机技术应用于异步电机的控制系统中,设计了基于LabVIEW的异步电机测试系统,介绍了该系统的硬件、软件构成及实现方法。利用LabVIEW作为上位机监控软件,结合西门子S7-300PLC实现了对异步电机测试过程的实时监控;同时在LabVIEW中使用OPC技术与PLC进行通讯以实现上位机对执行电机的控制。     

基于GPIB接口的功率测试系统开发与设计

介绍了基于GPIB接口和LabVIEW软件平台组建功率测试系统的方法.所设计的测试系统通过GPIB接口总线实现PC机与功率测试仪器PZ4000之间的通讯和对仪器的控制.详细介绍了测试系统的硬件构成、应用程序设计思路及具体的实现方法.该系统已在实际应用中取得很好的效果,提高了功率测试的自动化程度、测试效率和精度,易于扩展.     

基于LabVIEW的智能TAS传感器测试系统设计

针对线控转向用智能TAS传感器复杂性能的检测需求，研究分析了传感器的基本原理，利用USBCAN接口、STM32模块和伺服电机等硬件搭建了基于LabVIEW的传感器测试系统。系统以调用动态链接库TSMaster.dll函数的方式进行上位机和下位机之间的串口通信，实现了对传感器运行工况的模拟，并利用智能汽车接口实现了智能TAS传感器的协议解析，在LabVIEW开发环境中采用通知器模式实现了传感器与伺服电机信号的同步采集，同时设计了离散傅里叶分析、转角游标算法等数据分析模块对采集到的信号进行处理。测试数据表明，传感器扭矩信号输出偏差始终保持在±0.15°范围内，方向盘转角误差在±0.7°范围内，所设计的测试系统能在理想范围内对智能TAS传感器进行扭矩和转角性能的复合式测量，加快了厂商研发以及投产的进度，具有实际应用价值。     

Steady-state somatosensory evoked potentials: suitable brain signals for brain-computer interfaces?

One of the main issues in designing a brain-computer interface (BCI) is to find brain patterns, which could easily be detected. One of these pattern is the steady-state evoked potential (SSEP). SSEPs induced through the visual sense have already been used for brain-computer communication. In this work, a BCI system is introduced based on steady-state somatosensory evoked potentials (SSSEPs). Transducers have been used for the stimulation of both index fingers using tactile stimulation in the "resonance"-like frequency range of the somatosensory system. Four subjects participated in the experiments and were trained to modulate induced SSSEPs. Two of them learned to modify the patterns in order to set up a BCI with an accuracy of between 70% and 80%. Results presented in this work give evidence that it is possible to set up a BCI which is based on SSSEPs.     

EEG based BCI-towards a better control. Brain-computer interface research at Aalborg University.

This paper summarizes the brain-computer interface (BCI)-related research being conducted at Aalborg University. Namely, an online synchronized BCI system using steady-state visual evoked potentials, and investigations on cortical modulation of movement-related parameters are presented.     

Brain-Computer Interfaces Based on Visual Evoked Potentials

Recently, electroencephalogram (EEG)-based brain? computer interfaces (BCIs) have become a hot spot in the study of neural engineering, rehabilitation, and brain science. In this article, we review BCI systems based on visual evoked potentials (VEPs). Although the performance of this type of BCI has already been evaluated by many research groups through a variety of laboratory demonstrations, researchers are still facing many difficulties in changing the demonstrations to practically applicable systems. On the basis of the literature, we describe the challenges in developing practical BCI systems. Also, our recent work in the designs and implementations of the BCI systems based on steady-state VEPs (SSVEPs) is described in detail. The results show that by adequately considering the problems encountered in system design, signal processing, and parameter optimization, SSVEPs can provide the most useful information about brain activities using the least number of electrodes. At the same time, system cost could be greatly decreased and usability could be readily improved, thus benefiting the implementation of a practical BCI.     

Brain-computer interfaces based on the steady-state visual-evoked response.

The Air Force Research Laboratory has implemented and evaluated two brain-computer interfaces (BCI's) that translate the steady-state visual evoked response into a control signal for operating a physical device or computer program. In one approach, operators self-regulate the brain response; the other approach uses multiple evoked responses.     

用于脑机接口的感觉刺激事件相关电位研究进展

脑机接口研究的目的就是在人脑和计算机或其他电子设备之间建立一种直接联系,使人们可以通过思维来直接控制计算机或外部设备。感觉刺激诱发的事件相关电位是基于脑电的脑机接口系统研究中备受关注的一种信号模式,按其刺激模式的不同又可分为视觉、听觉、体感等单一感觉通道刺激诱发的和跨感觉通道刺激诱发的事件相关电位。事件相关电位研究的发展表明：相对于单一感觉通道,跨感觉通道刺激诱发的事件相关电位具有波幅高、潜伏期短且含有高维度空间分布信息的特点,可弥补单一感觉诱发事件相关电位信息过少、不利识别的缺陷,从而提高信息转化速度和分类准确率,在脑机接口中具有更高的实用价值。     

A practical VEP-based brain-computer interface.

This paper introduces the development of a practical brain-computer interface at Tsinghua University. The system uses frequency-coded steady-state visual evoked potentials to determine the gaze direction of the user. To ensure more universal applicability of the system, approaches for reducing user variation on system performance have been proposed. The information transfer rate (ITR) has been evaluated both in the laboratory and at the Rehabilitation Center of China, respectively. The system has been proved to be applicable to > 90% of people with a high ITR in living environments.     

Enhancement of steady‐state visual evoked potential‐based brain–computer interface systems via a steady‐state motion visual stimulus modality

Steady‐state visual evoked potential (SSVEP)‐based brain–computer interface (BCI) systems are among the most accurate assistive devices for patients with severe disabilities. However, existing visual stimulation patterns lead to eye fatigue, which affects the system performance. Therefore, in this study, we propose two improvements to SSVEP‐based BCI systems. First, we propose a novel visual stimulator that incorporates a visual motion stimulus for the steady‐state visual stimulus to reduce eye fatigue while maintaining the advantages associated with SSVEPs. We also propose two corresponding feature extraction algorithms, i.e. SSVEP detection and visual attention detection, to capture the phenomena of steady‐state motion visual stimulus responses. The accuracy of the test was ∼83.6%. Second, we propose a novel hybrid BCI‐SSVEP system and a motion visual stimulus hybrid BCI system to enhance the SSVEP‐based BCI system during a state of eye fatigue. Participants used the SSVEP system until reaching a fatigued state and then began using a hybrid motion visual stimulus. The accuracy of the proposed system was ∼85.6%. The proposed improvements can be incorporated into practical BCI systems for wheelchair control. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.