基于LabVIEW运动想象的脑机接口系统

背景：基于事件相关电位的脑-机接口,可广泛应用于残障患者的康复,显示出其重要性和未来实现的可行性。目的：提出基于LabVIEW环境下的运动想象脑-机接口系统的实现方案。方法：研究的关键部分是视觉刺激器的设计和脑电特征信号的特征提取两部分。测试者通过观察视觉刺激器上的左右手连续播放图像刺激产生脑电信号,采用带通滤波提高信噪比,用滑动窗截取脑电数据并且对截取的数据从能量的角度分析得到运动想象特征,同时可以在线提取特征,为实现实时系统打下了基础。结果与结论：该方案能有效地提取出运动想象特征,并且通过离线模式识别进行了有效的分类,分类效果达到了82%。     

基于多通道自适应自回归模型脑-机接口系统特征的提取

背景:由于脑电图信号的非平稳特性,脑-机接口系统至今仍然没有走出实验室,制约脑-机接口实用的主要原因之一是由于被试生理或心理状态的干扰下,脑电特征信号动态变化,难以得到稳定可靠的分类特征。目的:观察动态提取基于左手、右手和脚3种运动想象时的脑电信号分类特征,提高在线脑-机接口系统分类准确率和反应速度。方法:共有3位自愿受试者参加了实验,按照屏幕上的提示分别想象左手、右手和脚3种运动,对采集到的脑电图信号,首先通过带通及拉普拉斯滤波,去除眼电等干扰;其次提取改进的多变量自适应自回归模型模型参数作为分类特征;最后与传统的自适应自回归模型和自回归模型方法进行了比较。结果与结论:结果表明改进的多通道自适应自回归模型算法能够比较稳定的提取出对应左手、右手和脚的分类特征,有利于进一步改进在线脑-机接口数据分析算法的自适应能力,促进脑-机接口系统的实际应用。     

基于多通道自适应自回归模型脑-机接口系统特征的提取

背景：由于脑电图信号的非平稳特性,脑-机接口系统至今仍然没有走出实验室,制约脑-机接口实用的主要原因之一是由于被试生理或心理状态的干扰下,脑电特征信号动态变化,难以得到稳定可靠的分类特征。目的：观察动态提取基于左手、右手和脚3种运动想象时的脑电信号分类特征,提高在线脑-机接口系统分类准确率和反应速度。方法：共有3位自愿受试者参加了实验,按照屏幕上的提示分别想象左手、右手和脚3种运动,对采集到的脑电图信号,首先通过带通及拉普拉斯滤波,去除眼电等干扰;其次提取改进的多变量自适应自回归模型模型参数作为分类特征;最后与传统的自适应自回归模型和自回归模型方法进行了比较。结果与结论：结果表明改进的多通道自适应自回归模型算法能够比较稳定的提取出对应左手、右手和脚的分类特征,有利于进一步改进在线脑-机接口数据分析算法的自适应能力,促进脑-机接口系统的实际应用。     

基于功率谱峰值及时变线性分类算法的运动意识分类

背景:脑电信号的特征提取是脑机接口系统中一个重要的环节,如何快速有效地提取反映大脑意识任务状态的脑电特征是进行分类、正确解读意识任务的关键.目前,提取脑电信号特征通常采用功率谱密度估计、自回归模型和小波变换等方法,这些特征都是以脑电信号的线性化为前提,上述方法不能很好地反映出大脑的非线性动力学性质.目的:分析脑电信号功率谱峰值在识别左右手想象运动中的作用.方法:采用脑机接口2003竞赛中Graz科技大学提供的脑电数据,用小波包分解获取8～24 Hz脑电信号,计算C3,C4电极脑电信号的功率谱峰值作为脑电特征向量,运用时变线性分类算法对运动意识任务运行分类.结果与结论:对140次实验的测试样本进行数据分析,最大分类正确率可达89.29%,最大互信息和信噪比分别为0.6269 bit和1.3848.C3,C4电极8～24 Hz脑电信号功率谱峰值能很好地反映左右手运动想象脑电特征的变化,与事件相关去同步/事件相关同步现象变化一致,可在线识别左右手想象运动.     

脑机接口视觉刺激器的研究

目的:研究基于视觉诱发电位的脑机接口视觉刺激器。方法:根据视觉的基本特性阐明了视觉诱发电位用于脑机接口的原理,采用计算机编程,在计算机屏幕上产生多种刺激模式,以闪烁的不同小块代表多种可能的选择,受试者注视其中一个目标,分析诱发电位可判别受试者所注视的目标。结果:该方案能有效地诱发出可识别的具有特征性的视觉诱发电位。结论:该视觉刺激器能产生多种刺激模式,能满足脑机接口实验要求。     

基于混沌机制BP神经网络的左右手运动识别算法

目的：想象动作提取是脑-机接口技术的关键和难点之一,特征分类是脑-机接口研究的一个重要方面,同时也是一个薄弱环节.想象左（右）手运动和实际做这个运动会以同样的方式改变大脑主要感觉运动区域的神经活动,引起脑电相关频率成分的特征变化. 方法：及时有效的提取和识别这些与运动想象相关的脑电模式,可以帮助严重瘫痪患者控制光标或辅助设备以替代其受损的运动功能,建立一种与外界交流沟通的新途径.研究表明,通过神经网络进行特征分类能产生比较高的精度. 结果：采用基于混沌机制BP神经网络的左右手运动识别算法,将混沌控制引入常规BP算法,利用混沌机制固有的全局游动,逃出权值优化过程中存在的局部极小点,最终使权值进入全局意义下的最优不动点的某邻域内,解决了网络训练易陷入局部极小点的问题. 结论：仿真结果表明该算法快速有效,优于常规BP算法,有效的提高了控制精度,从而验证了混沌机制神经网络技术在脑-机接口特征分类算法中的优势.     

基于时频域分析的运动想象脑电信号分类

人的不同运动想象会产生不同的脑电信号.脑机接口系统就是利用这种不同的脑电信号,利用外部的连接和控制设备将不同的思维活动与不同的指令结合起来,实现人脑和外部设备的通信.为了从包含各种噪声的脑电信号中提取特征,国内外学者运用各种方法,通过多种途径,力图达到最优的信号分类模式.文章介绍了一种新的方法运用于运动想象脑电信号分类,该方法基于脑电信号的时频域分析,结合C3,C4电极脑电信号间的相互关系,依据Fisher距离进行特征抽取,运用线性分类器进行分类.该算法运用到3名受试者的脑电数据中,分别对选取脑电信号特征频率段、Kappa值、和脑电信号特征选取不同时间段进行分析.分类效果因受试者而异,从65.0%到93.1%.     

脑机接口视觉刺激器的研究

目的：研究基于视觉诱发电位的脑机接口视觉刺激器。方法：根据视觉的基本特性阐明了视觉诱发电位用于脑机接口的原理，采用计算机编程，在计算机屏幕上产生多种刺激模式，以闪烁的不同小块代表多种可能的选择，受试者注视其中一个目标，分析诱发电位可判别受试者所注视的目标。结果：该方案能有效地诱发出可识别的具有特征性的视觉诱发电位。结论：该视觉刺激器能产生多种刺激模式，能满足脑机接口实验要求。     

基于Mu/Beta节律想象运动脑电信号特征的提取

背景:不同的运动会产生不同的脑电信号,脑机接口技术就是利用脑电信号的特异性,通过现代信号处理技术和外部的连接实现人脑与外部设备的通信.以实现脑机接口在线研究的目标,首先要解决的是脑电信号处理的速度问题.目的:研究快速、准确地提取脑电信号特征及分类的方法.方法;充分利用想象运动过程中,脑电信号中Mu/Beta节律的事件相关同步化和去同步化特性,以2003年BCI竞赛数据为处理对象,采用带通滤波和小波包分析的方法提取Mu、Beta节律,提取C3、C4两通道上的能量平均值形成二维特征向量,利用matlab自带的classify函数进行分类.结果与结论:通过对训练数据进行测试得到较为合适的参数,利用该参数对同等条件下的训练数据和测试数据分别进行判别,分类正确率分别达到87.857%和88.571%.     

基于脑电alpha波及运动想象的在线脑机接口系统设计

背景:目前在线脑机接口系统绝大多数采用同步式设计,无法区分"工作"状态与"空闲"状态。目的:设计一种能够自由在"工作"与"空闲"状态间切换,方便灵活的脑机接口系统。方法:设计了综合睁眼产生的alpha波阻断现象,以及进行运动想象时产生事件相关同步及去同步现象这些生理特征的在线脑机接口系统。通过检测使用者枕部脑电信号alpha波状况,来切换"空闲"与"工作"状态;在"工作"状态下,通过想象不同的肢体运动,分析运动皮质脑电信号的频率特征,来实现对外界的信息传输。结果与结论:实验证明,经过训练的使用者在该在线脑机接口平台上可以自如的在不同状态间进行切换,并且能以很高的分类正确率发出控制命令。采用此方法进行设计,脑机接口系统的实用性得到了增强。     

Effectiveness of a behavioral change intervention in Thai elders after knee replacement

BACKGROUND: After total knee replacement, elders need an effective intervention to change exercise and physical activity behavior. OBJECTIVES: This study examined the effects of a behavioral change intervention (BCI) on self-efficacy and outcome expectations for exercise and functional activity, physical activity participation, and physical performance of older adults. METHODS: The study was based on the social cognitive theory (SCT), with a longitudinal quasi-experimental, pretest-posttest control group design. Sixty-three Thai elders undergoing knee replacement surgery were studied. The experimental group received a BCI based on SCT given by the investigator. Outcome measures were the Self-Efficacy for Exercise Scale (SEES) and Self-Efficacy for Functional Activity Scale (SEFAS), the Outcome Expectations for Exercise Scale (OEES) and Outcome Expectations for Functional Activity Scale (OEFAS), the Physical Performance Test (PPT), and the Physical Activity Diary (PAD). RESULTS: The experimental group had significantly greater improvements in self-efficacy for exercise, outcome expectations for exercise, and functional activity, significantly more participation in exercise and walking, and significantly greater improvement in physical performance than did the control group at postoperative weeks 2 and 6. DISCUSSION: The BCI based on SCT was effective in changing the outcomes in the expected direction. This BCI may be applicable, with modifications, to elders in other situations in which changing behavior is the key to recovery.     

基于四类运动想象任务的脑电信号识别

背景:脑-机接口是在大脑与外部设备之间建立的直接的交流通路,基于运动想象的脑-机接口研究已经从两类运动想象任务的识别发展到多类任务的识别。目的:探寻准确有效的对多任务运动想象脑电信号进行特征提取及模式识别的方法。方法:首先采用公共平均参考法减小多通道中各导联间的相关性,提高脑电信号的信噪比。并对公共空间模式算法进行扩展,采用"一对多"的策略,对4类任务的脑电信号进行特征提取,在模式识别过程中,采用基于决策树法的支持向量机进行分类。对于实验对象样本不充足,结合支持向量机和贝叶斯分类器,将分类结果中具有大概率的测试样本扩充到训练集,最后再次运用支持向量机进行分类。结果与结论:最佳正确率达到92.78%,"一对多"的公共空间模式和基于决策树的支持向量机可以有效地进行多任务脑电信号识别,扩充样本可以提高分类正确率。     

A plug-and-play brain-computer interface to operate commercial assistive technology

Abstract

Purpose: To determine if a brain-computer interface (BCI) could be used as a plug-and-play input device to operate commercial assistive technology (AT), and to quantify the performance impact of such operation. Method: Using a hardware device designed in our lab, participants (11 with amyotrophic lateral sclerosis, 22 controls) were asked to operate two devices using a BCI. Results were compared to traditional BCI operation by the same users. Performance was assessed using both accuracy and BCI utility, a throughput metric. 95% confidence bounds on performance differences were developed using a linear mixed model. Results: The observed differences in accuracy and throughput were small and not statistically significant. The confidence bounds indicate that if there is a performance impact of using a BCI to control an AT device, the impact could easily be overcome by the benefits of the AT device itself. Conclusions: BCI control of AT devices is possible, and the performance difference appears to be very small. BCI designers are encouraged to incorporate standard outputs into their design to enable future users to interface with familiar AT devices.

• Implications for Rehabilitation

• Brain-computer interface (BCI) control of assistive technology (AT) devices is possible.

• The performance impact of such control is low when BCIs are commercially available, AT providers can use a BCI as an input device to existing AT devices already in use by their clients.

     

BAEP转颈试验在后循环缺血诊断中的应用

目的：探讨脑干听觉诱发电位（BAEP）转颈试验对后循环缺血的诊断意义。方法：对60例后循环缺血眩晕间歇期患者分别作BAEP常规检测和转颈试验，并与40例正常人对照。结果：后循环缺血组BAEP常规检测阳性率26．7％，转颈试验阳性率91．7％，与对照组比较均有极显著差异。结论：转颈试验可提高BAEP的阳性率，对后循环缺血诊断有重要参考意义。     

Can we explain running-related injury preventive behavior? A path analysis

BackgroundBehavioral and social science theories/models have been gaining attention in sports injury prevention.ObjectiveTo investigate the potential of the Theory of Planned Behavior in explaining running-related injury preventive behavior.MethodsSix-month prospective cohort study based on data gathered from a randomized controlled trial. From a total of 1512 invited trail runners, 232 were included in this study. Preventive behaviors and their determinants were assessed at baseline and two and six months after baseline. Five-point Likert scales were used to assess the determinants of preventive behavior. A Bayesian path analysis was conducted applying mixed models and mediation analysis.ResultsA 1-point increase in intention, attitude, subjective norm, and perceived behavioral control predicted an increase of 54% (95% Bayesian credible interval [BCI]: 38, 71) in the rate of performing running-related injury preventive behavior, explaining 49% (R² 0.49; 95% BCI: 0.41, 0.56) of the variance around preventive behavior. Intention and perceived behavioral control predicted running-related injury preventive behavior directly, while 40% (95% BCI: 21, 61) and 44% (95% BCI: 20, 69) of the total effect of attitude was mediated by intention and perceived behavioral control, respectively. Attitude, subjective norm, and perceived behavioral control predicted intention.ConclusionsThe Theory of Planned Behavior may have the potential to explain half of the variance around running-related injury preventive behavior and intention. Therefore, such theory may be considered a relevant and useful tool in developing, investigating, and/or implementing programs aimed at preventing running-related injuries.     

Application of BCI systems in neurorehabilitation: a scoping review

Purpose: To review various types of electroencephalographic activities of the brain and present an overview of brain–computer interface (BCI) systems’ history and their applications in rehabilitation. Methods: A scoping review of published English literature on BCI application in the field of rehabilitation was undertaken. IEEE Xplore, ScienceDirect, Google Scholar and Scopus databases were searched since inception up to August 2012. All experimental studies published in English and discussed complete cycle of the BCI process was included in the review. Results and discussion: In total, 90 articles met the inclusion criteria and were reviewed. Various approaches that improve the accuracy and performance of BCI systems were discussed. Based on BCI’s clinical application, reviewed articles were categorized into three groups: motion rehabilitation, speech rehabilitation and virtual reality control (VRC). Almost half of the reviewed papers (48%) concentrated on VRC. Speech rehabilitation and motion rehabilitation made up 33% and 19% of the reviewed papers, respectively. Among different types of electroencephalography signals, P300, steady state visual evoked potentials and motor imagery signals were the most common. Conclusions: This review discussed various applications of BCI in rehabilitation and showed how BCI can be used to improve the quality of life for people with neurological disabilities. It will develop and promote new models of communication and finally, will create an accurate, reliable, online communication between human brain and computer and reduces the negative effects of external stimuli on BCI performance.

• Implications for Rehabilitation

• The field of brain–computer interfaces (BCI) is rapidly advancing and it is expected to fulfill a critical role in rehabilitation of neurological disorders and in movement restoration in the forthcoming years.

• In the near future, BCI has notable potential to become a major tool used by people with disabilities to control locomotion and communicate with surrounding environment and, consequently, improve the quality of life for many affected persons.

• Electrical field recording at the scalp (i.e. electroencephalography) is the most likely method to be of practical value for clinical use as it is simple and non-invasive. However, some aspects need future improvements, such as the ability to separate close imagery signal (motion of extremities and phalanges that are close together).

     

A clinical screening protocol for the RSVP Keyboard brain–computer interface

Purpose: To propose a screening protocol that identifies requisite sensory, motor, cognitive and communication skills for people with locked-in syndrome (PLIS) to use the RSVP Keyboard? brain–computer interface (BCI). Method: A multidisciplinary clinical team of seven individuals representing five disciplines identified requisite skills for the BCI RSVP Keyboard?. They chose questions and subtests from existing standardized instruments for auditory comprehension, reading and spelling, modified them to accommodate nonverbal response modalities, and developed novel tasks to screen visual perception, sustained visual attention and working memory. Questions were included about sensory skills, positioning, pain interference and medications. The result is a compilation of questions, adapted subtests and original tasks designed for this new BCI system. It was administered to 12 PLIS and 6 healthy controls. Results: Administration required 1?h or less. Yes/no choices and eye gaze were adequate response modes for PLIS. Healthy controls and 9 PLIS were 100% accurate on all tasks; 3 PLIS missed single items. Conclusions: The RSVP BCI screening protocol is a brief, repeatable technique for patients with different levels of LIS to identify the presence/absence of skills for BCI use. Widespread adoption of screening methods should be a clinical goal and will help standardize BCI implementation for research and intervention.

• Implications for Rehabilitation

• People with locked-in syndrome must have certain sensory, motor, cognitive and communication skills to successfully use a brain–computer interface (BCI) for communication.

• A screening profile would be useful in identifying potentially suitable candidates for BCI.