联合的范围内进行的研究资讯及通讯科技有针对性的计划 - 信通空，由法国国家科学研究中心，INRIA和DST支持下CEFIPRA的保护伞。笔者想感谢的学生，特别是Rahima Sidiboulenouar，RISHABH塞加尔，并且Gorish AGGARWAL的支持，对实验装置的开发。

注意:HMI软件管道的基础上开发的免费的开源软件，并在关闭的，现成的低成本视频游戏传感器（详细信息:https://team.inria.fr/nphys4nrehab/software/和https: //github.com/NeuroPhys4NeuroRehab/JoVE）。该HMI软件管道在基于虚拟现实的游戏平台为visuomotor平衡疗法（VBT）8修改功能范围的任务（mFRT）21时提供的数据收集。 图2a示出了诊断眼跟踪器设置，其中所述视线特征为脑卒中后的残余函数的量化，使得在虚拟现实的视觉反馈可以相应地定制离线萃取。 图2b示出了用于VBT的实验装置。 <img alt="图2" src="/files/ftp_upload/52394/52394fig2.jpg" /> 图2:（ <str翁&gt;一）人机界面，用于中风后追求眼球运动的评价示意图。 （b）该人机界面，其中所述软件接口整合生物信号传感器和运动捕捉到记录与神经肌肉电刺激系统（NMES）和感官电刺激（SES），用于中风后NMES移动脑/体成像数据的示意图/ SES辅助visuomotor平衡疗法。 NMES:神经肌肉电刺激，SES:感官电刺激，肌电图检查:肌电图，脑电图:脑电图，EOG:电图，扶贫:压力的中心，PC:个人计算机。从8和37再现。 <a href="https://www.jove.com/files/ftp_upload/52394/52394fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 1.软件安装移动脑/体成像VBT在<ol><li>安装用于运动司机帽TURE（在https://code.google.com/p/labstreaminglayer/wiki/KinectMocap提供的安装程序） <ol><li>下载并安装http://go.microsoft.com/fwlink/?LinkId=253187 Kinect的运行（运动捕捉传感器不应插入任何USB端口的计算机上）。 </li><li>插上动力运动捕捉传感器进入通过接口电缆的USB端口。驱动程序会自动加载。 </li></ol></li><li>安装驱动程序的眼动仪感应器（在提供安装过程<a href="http://github.com/esdalmaijer/EyeTribe-Toolbox-for-Matlab">http://github.com/esdalmaijer/EyeTribe-Toolbox-for-Matlab</a> ） <ol><li>从http://theeyetribe.com下载软件，启动应用程序并启动安装软件应用程序（眼动仪传感器不应插入任何USB端口的计算机上）。 </li><li>插上电眼动仪传感器和驱动程序将自动加载。 </li></ol></li><li>研究所所有驱动程序的平衡板（在规定（在http://www.colorado.edu/intphys/neuromechanics/cu_wii.html提供的安装程序安装程序） <ol><li>下载并从http://www.colorado.edu/intphys/neuromechanics/CU_WiiBB.zip提取CU_WiiBB.zip </li><li>复制WiiLab文件夹微软windows操作系统的标准Program Files目录。 </li><li>打开WiiLab文件夹中的Program Files目录，并以管理员身份运行的InstallWiiLab.bat文件安装平衡板。 </li></ol></li><li>安装（在http://openvibe.inria.fr/how-to-connect-emotiv-epoc-with-openvibe/提供的安装程序）脑电/眼电驱动<ol><li>下载并安装http://www.emotiv.com/apps/sdk/209/ SDK Emotiv公司</li><li>下载并安装https://code.google.com/p/labstreaminglayer/downloads/detail?name=OVAS-withLSL-0.14.3-3350-svn.zip与labstreaminglayer（LSL）OpenViBE采集服务器的分布式多SEnsor信号传输，时间同步和数据采集系统（在https://code.google.com/p/labstreaminglayer/提供的安装程序）。 </li></ol></li><li>安装用于商业NMES刺激（在http://www.vivaltis.com/gammes/phenix/phenix-usb-neo-50-554-1.html#content详细信息）的驱动程序。 </li></ol> 2.低成本传感器的位置移动脑/身体成像（MOBI）:开源人机界面软件管道为移动脑/身体成像（MOBI）19低成本关闭现有的传感器（图2b），它可以适用于其他敏捷性训练计划。 <ol><li>为MOBI可视反馈: <ol><li>通过获得一个投影屏幕以显示在房间的一端的视觉生物反馈开始（推荐从受试者0.6米距离）。 </li><li>调节高度，使屏幕的中心将在受试者的眼平。 </li></ol></li><li>为MOBI动作捕捉: <ol><li>将运动CApture传感器在投影屏幕的正前方，并在动作捕捉容积瞄准它。 </li><li>确认动作捕捉的体积在动作捕捉传感器前面1.5米2.5米。 </li></ol></li><li>平衡板放置的MOBI: <ol><li>放置在地板上的平衡板，约2.0米的动作捕捉传感器路程。 </li><li>周围留出平衡板足够的空间，以确保（改性功能到达任务21时即 ）全身运动。 </li></ol></li><li> EEG / EMG / EOG传感器配置为MOBI <ol><li>让拍摄对象坐在面临的动作捕捉一把椅子，用自己的平衡板脚。 </li><li>放置在记录（EMG）暨刺激（NMES / SES）双侧电极上主体的内侧腓肠肌（MG）和胫骨前（TA）的肌肉。然后，将它们连接到无线电刺激（NMES / SES）系统。 </li><li>广场上的主题的脑电图（EEG）帽头部国际10以下 - 20系统。然后，将电极脑电图与-Fz，C3，CZ，C4，P3，Pz的，P4，PO7，奥兹，PO8导电膏 - 它们连接到无线耳机脑电图之前。 </li><li>将上述导电浆料和下方的眼睛垂直EOG之一的两名脑电图电极，把两个电极用导电浆料在每只眼睛的水平EOG外眦。 （注:如果眼睛跟踪传感器未在中风后受试者使用，那么双边EOG被优选）。 </li><li>将两个电极脑电图耳垂上作为参考电极。 </li></ol></li></ol>中风后追求眼动3.眼动仪基础的评估<ol><li>让拍摄对象坐在一起下巴搁在舒适的高度可调展休息。然后，提高计算机显示器到一个方便的高度，使得眼睛大致朝向计算机显示器（ 图2a）的中心。 </li><li>将眼动仪 - [R<html>从展休息oughly50厘米，并要求受直视计算机屏幕上的视觉线索。 </li><li>在"慧眼"文件夹校准眼动仪传感器运行EyeTribeWinUI.exe。受试者将被要求看一下电脑屏幕上的各种目标大约每2秒。一个典型的用户校准过程大约需要20秒才能完成。被检者的凝视点的（X，Y）坐标被记录为用于校准不同线索的目标。 </li><li>运行"Visual_Stimulus.exe"的慧眼文件夹中执行虚拟现实基础接口。随后运行中存在的"慧眼"文件夹来获取与该虚拟现实基于任务同步的受试者的眼睛注视数据"SmartEye.exe"计划。这个数据将用于中风后追求眼球运动的评估。 </li></ol>2394fig3.jpg"/&gt; 图3:（ 一 ）表示压力（COP）的中心，需要visuomotor平衡疗法期间volitionally驱动到线索目标光标，（ 二 ）Visuomotor平衡疗法协议，其中受试者拨转计算机光标被驱动的外围设备的目标volitionally产生的扶贫之旅。复位可以用神经肌肉电刺激（NMES）和感官电刺激（SES），（ 三 ）视觉线索visuomotor平衡疗法实验装置的协助。从8和37再现。 <a href="https://www.jove.com/files/ftp_upload/52394/52394fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> MOBI下4. NMES / SES辅助Visuomotor平衡疗法（VBT） <ol><li>连接眼球跟踪器和平衡板传感器到视觉反馈计算机（ 网络连接古尔2）。 <ol><li>确保眼动仪传感器通电，连接到电脑，而且它完全启动。启动"EyeTribe SERVER.EXE&#39;和&#39;EyeTribeWinUI.exe"可在"VBT"文件夹（见步骤1.3）。 </li><li>确保平衡板传感器的电源。然后，按在平衡板传感器按钮使菜单中的远程发现。然后，点击系统任务栏中显示或隐藏图标，点击蓝牙设备图标。然后，点击"添加设备"选项，然后配对平衡板传感器作为蓝牙设备不使用代码的视觉反馈的计算机。一旦平衡板传感器连接到视觉反馈的电脑，打开"VBT"文件夹，然后运行WiiBBinterface.m文件建立Matlab-平衡板传感器接口（见步骤1.6）。 </li><li>确保动作捕捉传感器上电后，连接到电脑，它完全启动（有一个绿色前面的LED）。打开LSL文件夹并启动"动作捕捉"软件，开始动作捕捉传感器数据流的（见步骤1.6）。 </li><li>确保EEG / EOG数据采集系统的供电。然后，在现有的LSL文件夹openvibe采集服务器 - withlsl.cmd双击（见步骤1.6）。从菜单中选择相应的传感器硬件（ 即 "Emotiv公司EPOC"），并配置模块，如果有必要，通过单击"驱动程序属性"。然后，点击"连接"，然后点击"播放"开始采集服务器。 </li></ol></li><li>用于校准的VBT传感器<ol><li>问卒中后受站在平衡板与安全吊带（和部分体重支持，如果需要的话）。 </li><li>设置必要根据临床观察垂直竖立的最小基线NMES水平（脉冲宽度和电流值）（ 即 ，零体重支持）22。用于设置的最小基线NMES水平，人们可以在20Hz设定的刺激频率和然后增加脉冲宽度和/或电流电平，直到直立实现。这里，膝伸肌NMES需要产生足够的扭矩，以防止膝盖屈曲。 </li><li>让拍摄对象进行影响COM和COP位置不同的范围动作。 </li><li>为了收集多传感器校准数据，而主体执行各种自发最大覆盖不同的方向，影响质量中心（COM）的运动和压力中心运行的可用&#39;CalibSensors.m"节目中的"DataCollect&#39;夹在视觉反馈（COP）的位置。 </li></ol></li></ol>从低成本传感器5.多传感器数据采集VBT在（图2b） <ol><li>在"DataCollect"文件夹中运行"CollectBaseline.m"程序来收集基线休息-state，眼睛开，多传感器通过询问受静置2分钟，而在PC显示器（ 图3a）在扶贫目标直视数据。 </li><li>视觉反馈计算机的视频输出连接到投影屏幕，并运行在"VBT"文件夹中的文件SmartEyeVRTasks.exe在视觉反馈计算机启动SmartEyeVRTasks GUI。此外，在"DataCollect"文件夹中运行"CollectVBT.m"计划期间VBT收集传感器数据。 <ol><li>从直立，称为"中央保持"阶段，要求受操纵光标，由缔约方会议推动下，以最快的速度向随机赠送外设目标通过视觉反馈线索（ 图3b）。 </li><li>在此之后&#39;移动&#39;的阶段，让拍摄对象在"外设保持"阶段以1秒的目标位置，按住鼠标。 </li><li>继"外设保持"阶段，将光标"<html> ;复位&#39;回到中心时，主体需要返回到直立 - "中心保持"位置。 NMES / SES被触发肌肉时，其肌电图级别必须高于设定的阈值，以协助缔约方会议返回到"中央保持"位置所需的意志努力。 注意:mFRT的难度可以增加通过减小增益， <img alt="式（1）" src="/files/ftp_upload/52394/52394eq1.jpg" />或增加的噪声方差， <img alt="公式（2）" src="/files/ftp_upload/52394/52394eq2.jpg" /> ，主题明确可行的范围内: <img alt="公式3" src="/files/ftp_upload/52394/52394eq3.jpg" /> 那里的扶贫游览， <img alt="公式4" src="/files/ftp_upload/52394/52394eq4.jpg" /> ，带动了电脑光标， <img alt="公式5" src="/files/ftp_upload/52394/52394eq5.jpg" />在离散时间， <img alt="公式6" src="/files/ftp_upload/52394/52394eq6.jpg" />与时间步，7"SRC ="/文件/ ftp_upload / 52394 / 52394eq7.jpg"/&gt;。 </li></ol></li></ol>

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Neuroergonomics and Operational. , 749-758 (2009).</li><li>Ojeda, A., Bigdely-Shamlo, N., Makeig, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MoBILAB:+an+open+source+toolbox+for+analysis+and+visualization+of+mobile+brain/body+imaging+data.">MoBILAB: an open source toolbox for analysis and visualization of mobile brain/body imaging data.</a> Frontiers in Human Neuroscience. 8, 121 (2014).</li><li>Dutta, A., Chugh, S., Banerjee, A., Dutta, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Point-of-care-testing+of+standing+posture+with+Wii+balance+board+and+microsoft+kinect+during+transcranial+direct+current+stimulation:+A+feasibility+study.">Point-of-care-testing of standing posture with Wii balance board and microsoft kinect during transcranial direct current stimulation: A feasibility study.</a> NeuroRehabilitation. 34, 789-798 (2014).</li><li>Nataraj, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Feedback Control Of Standing Balance Using Functional Neuromuscular Stimulation Following Spinal Cord Injury. , (2011).</li><li>Dutta, A., Paulus, W., Nitsche, A., M, <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Translational+Methods+for+Non-Invasive+Electrical+Stimulation+to+Facilitate+Gait+Rehabilitation+Following+Stroke+-+The+Future+Directions.">Translational Methods for Non-Invasive Electrical Stimulation to Facilitate Gait Rehabilitation Following Stroke - The Future Directions.</a> Neuroscience and Biomedical Engineering. 1, 22-33 (2013).</li><li>Banerjee, A., Khattar, B., Dutta, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Low-Cost+Biofeedback+System+for+Electromyogram-Triggered+Functional+Electrical+Stimulation+Therapy:+An+Indo-German+Feasibility+Study.">A Low-Cost Biofeedback System for Electromyogram-Triggered Functional Electrical Stimulation Therapy: An Indo-German Feasibility Study.</a> ISRN Stroke. 2014, e827453 (2014).</li><li>Kerkhoff, G., Reinhart, S., Ziegler, W., Artinger, F., Marquardt, C., Keller, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Smooth+pursuit+eye+movement+training+promotes+recovery+from+auditory+and+visual+neglect:+a+randomized+controlled+study.">Smooth pursuit eye movement training promotes recovery from auditory and visual neglect: a randomized controlled study.</a> Neurorehabilitation and Neural Repair. 27, 789-798 (2013).</li><li>Carl, J. R., Gellman, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+smooth+pursuit:+stimulus-dependent+responses.">Human smooth pursuit: stimulus-dependent responses.</a> Journal of Neurophysiology. 57, 1446-1463 (1987).</li><li>Clark, R. A., Bryant, A. L., Pua, Y., McCrory, P., Bennell, K., Hunt, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validity+and+reliability+of+the+Nintendo+Wii+Balance+Board+for+assessment+of+standing+balance.">Validity and reliability of the Nintendo Wii Balance Board for assessment of standing balance.</a> Gait &amp; posture. 31, 307-310 (2010).</li><li>Clark, R. A., Pua, Y. -. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validity+of+the+Microsoft+Kinect+for+assessment+of+postural+control.">Validity of the Microsoft Kinect for assessment of postural control.</a> Gait &amp; posture. 36, 372-377 (2012).</li><li>Khattar, B., Banerjee, A., Reddi, R., Dutta, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Feasibility+of+Functional+Electrical+Stimulation-Assisted+Neurorehabilitation+following+Stroke+in+India:+A+Case+Series.">Feasibility of Functional Electrical Stimulation-Assisted Neurorehabilitation following Stroke in India: A Case Series.</a> Case Reports in Neurological Medicine. 2012, e830873 (2012).</li><li>Sailer, U., Flanagan, J. R., Johansson, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Eye-hand+coordination+during+learning+of+a+novel+visuomotor+task.">Eye-hand coordination during learning of a novel visuomotor task.</a> The Journal of neuroscience: the official journal of the Society for Neuroscience. 25, 8833-8842 (2005).</li><li>Herr, H., Popovic, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Angular+momentum+in+human+walking.">Angular momentum in human walking.</a> The Journal of Experimental Biology. 211, 467-481 (2008).</li><li>Taub, E., Morris, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Constraint-induced+movement+therapy+to+enhance+recovery+after+stroke.">Constraint-induced movement therapy to enhance recovery after stroke.</a> Current atherosclerosis reports. 3, 279-286 (2001).</li><li>Kasten, E., Wuest, S., Sabel, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Residual+vision+in+transition+zones+in+patients+with+cerebral+blindness.">Residual vision in transition zones in patients with cerebral blindness.</a> Journal of Clinical and Experimental Neuropsychology. 20, 581-598 (1998).</li><li>Marshall, S. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identifying+Cognitive+State+from+Eye+Metrics.">Identifying Cognitive State from Eye Metrics.</a> Aviation, Space, and Environmental Medicine. 78, 165-175 (2007).</li><li>Weerdesteyn, V., de Niet, M., van Duijnhoven, H. J. R., Geurts, A. C. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Falls+in+individuals+with+stroke.">Falls in individuals with stroke.</a> Journal of Rehabilitation Research and Development. 45, 1195-1213 (2008).</li><li>Stinear, C. M., Barber, P. A., Petoe, M., Anwar, S., Byblow, W. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+PREP+algorithm+predicts+potential+for+upper+limb+recovery+after+stroke.">The PREP algorithm predicts potential for upper limb recovery after stroke.</a> Brain: A Journal of Neurology. 135 ((Pt 8)), 2527-2535 (2012).</li><li>Dutta, A., Lahiri, D., Kumar, U., Das, A., Padma, M. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Post-stroke+engagement-sensitive+balance+rehabilitation+under+an+adaptive+multi-level+electrotherapy:+clinical+hypothesis+and+computational+framework.">Post-stroke engagement-sensitive balance rehabilitation under an adaptive multi-level electrotherapy: clinical hypothesis and computational framework.</a> Neuroscience and Biomedical Engineering. 2 (2), 68-80 (2015).</li></ol>

作者什么都没有透露。

运动和平衡疗法的简单，易用，临床有效的低成本的工具将在低资源设置为神经康复模式的转变。它很可能具有很高的社会影响，因为像中风神经系统疾病将在今后由于世界人口老龄化2急剧增加。还有就是，因此，迫切需要充分利用网络的物理系统中的能力，自定义，监控，支持远程站点神经康复最近成为可能通过电信计算，网络和物理过程的集成。为实现这一总体目标，中风后的追求?...

引起的脑，脊髓或视网膜梗死神经功能障碍的一个插曲叫脑卒中1。中风是一个全球性的健康问题和残疾全球1的第四大原因。在像印度和中国，世界上人口最多的两个国家的国家，因中风神经功能障碍被标记为隐藏疫情2。一中风后的最常见的医疗并发症的是具有高达73％的在第一年后中风3报告发病瀑布。在中风后下跌是多方面的，既包括脊柱脊髓上和因素，如平衡和视觉空间忽视4。通过Geurts并确定1同仁5综述）多方位受损最大重量双足站立，2）速度慢，3）定向的不精确性，和中移动4）单环子最大额面重量的变化如天平上小幅度因素秋天里SK。在日常活动所造成的影响可能是显著因为以前的作品表明，平衡与粗大运动功能5，6日间能力和独立性有关。此外，Geurts和同事5建议除了肌力脊髓上多感觉整合（和肌肉协调7）是用于其缺乏当前协议平衡恢复的关键。对多感觉整合，我们对volitionally驱动的非侵入性的电疗假设8（NMES / SES）的是，这个适应性行为可以被塑造和患肢，使的NMES / SES辅助运动中调节的感觉输入活跃知觉便利大脑可以招募交替运动通路9，如果需要，将这一信息反馈到后续的运动输出。 为了实现资源volitionally驱动NMES / SES辅助平衡训练国定贫困设定，低成本的人机界面（HMI）是通过利用现有的开源软件和最新进展在场外的现成的视频游戏传感器技术视觉听觉的生物反馈开发的。 NMES涉及已被证实可以改善肌肉强度和降低痉挛10神经和肌肉的协调电刺激。此外，SES涉及感觉神经的刺激电流唤起的感觉，其中前期发表的作品11表明应用subsensory刺激在胫前肌单是有效的衰减姿势摆动。在这里，人机将互动中风后平衡疗法，其中volitionally驱动NMES / SES的脚踝肌肉会作为一个肌肉放大器（与NMES），以及增强传入反馈（与SES）期间成为可能感觉运动统合协助健康脚踝战略12,13,14中姿势摇摆，以保持直立姿态。这是根据杜塔等 8提出的假设，即通过非侵入性的电疗影响相关的脚踝肌肉的增加皮质兴奋性，可能使踝关节僵硬的改善脊髓以上调制。事实上，先前的工作已经表明，NMES / SES引起在皮质兴奋性持久的变化，可能作为共活化运动和感觉纤维15,16的结果。此外，Khaslavskaia和Sinkjaer 17表明人类的存在NMES / SES的时间同步电机驱动皮质增强运动皮质兴奋性。因此，volitionally驱动NMES / SES可诱导脊髓反射短期的可塑性（ 例如 ，相互IA抑制17）其中，通过降途径给定的运动神经元池项目皮质神经元能抑制通过在IA-抑制性的对抗性运动神经元池人类18， 如图1，向邻perant调节模式（见杜塔等8）。 <img alt="图1" src="/files/ftp_upload/52394/52394fig1.jpg" /> 图1:概念（在杜塔细节等人 21）基本交互式人机界面（HMI）来驱动压力（COP）的中心光标移到提示的目标，以改善下volitionally驱动的神经肌肉电刺激踝关节肌肉协调（NMES） -assisted visuomotor平衡疗法脑电图:脑电图，MN:α-运动神经元，IN:IA-抑制中间神经元，肌电图检查:肌电图，DRG:背根神经节。从8和37再现。 <a href="https://www.jove.com/files/ftp_upload/52394/52394fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 该前 - 后（AP）的质量（COM）的中心位移进行通过踝plantarflexors（如内侧腓肠肌和比目鱼肌）和脊屈肌（如胫前肌），而内 - 外（ML）位移都受到脚踝反相器（例如胫前肌）和evertors（如腓骨长进行和肌肉芽孢）。因此，中风相关的脚踝损伤包括踝关节背屈肌肉无力，并增加了踝关节痉挛屈肌肌肉导致受损的姿势控制。这里，敏捷训练方案6可以在虚拟现实中利用（VR）基于游戏平台挑战动态平衡其中任务逐渐困难增大，这可能在预防跌倒6是比静态拉伸/重量移锻炼计划更为有效。例如，主题可以动态的平衡visuomotor任务，其中的难度，可以逐步提高到阿梅尔期间执行volitionally驱动NMES / SES协助AP和ML位移重量iorate卒中后特定的脚踝控制问题双足站立中移动。朝着一个资源贫乏的设置volitionally驱动NMES / SES辅助平衡疗法，我们提出这也可以从低用于数据收集低成本HMI移动脑/身体成像（MOBI）19，对视觉听觉生物反馈在MoBILAB离线数据的勘探成本的传感器（见奥赫达等 20）。

<table><tbody><tr><td>NMES stimulator</td><td>Vivaltis, France</td><td>PhenixUSBNeo</td><td>NMES stimulator cum EMG sensor (Figure 2b)</td></tr><tr><td>Balance Board</td><td>Nintendo, USA</td><td>Wii Balance Board</td><td>Balance Board (Figure 2b)</td></tr><tr><td>Motion Capture</td><td>Microsoft, USA</td><td>XBOX-360 Kinect</td><td>Motion Capture (Figure 2b)</td></tr><tr><td>Eye Tracker&amp;nbsp;</td><td>Eye Tribe</td><td>The Eye Tribe</td><td>SmartEye Tracker (Figure 2a)</td></tr><tr><td>EEG Data Acquisition System</td><td>Emotiv, Australia</td><td>Emotiv Neuroheadset</td><td>Wireless EEG headset (Figure 2b)</td></tr><tr><td>EEG passive electrode</td><td>Olimex</td><td>EEG-PE</td><td>EEG passive electrode for EOG and references (6 in number) (Figure 2b)</td></tr><tr><td>EEG active electrode</td><td>Olimex</td><td>EEG-AE</td><td>EEG active electrode (10 in number) (Figure 2b)</td></tr><tr><td>Computer with PC monitor</td><td>Dell</td><td></td><td>Data processing and visual feedback (Figure 2)</td></tr><tr><td>Softwares, EMG electrodes, NMES electrodes, and cables</td><td></td><td></td><td></td></tr></tbody></table>

a human-machine-interface integrating low-cost sensors with a neuromuscular electrical stimulation system for post-stroke balance rehabilitation

当在大脑中携带来自心脏血液的区域的动脉脉冲串或凝块阻碍血液流向脑部，从而防止氧和营养物质的递送中风引起。大约有一半的中风幸存者留下了某种程度的残疾。恢复性神经康复方法的创新迫切需要，以减少长期残疾。神经系统的重组其结构，功能和连接，以本征或外在刺激的响应的能力被称为神经可塑性。神经可塑性涉及脑卒中后功能障碍，而且在康复。有利neuroplastic改变可能与非侵入性的电疗变得容易，如神经肌肉电刺激（NMES）和感官电刺激（SES）。 NMES涉及运动神经和肌肉的协调电刺激电流的连续的短脉冲而SES invo激活它们感觉神经的LVES刺激导致从几乎没有感知到高度不愉快而变化的感觉电流。在这里，在康复过程积极皮质参与可能通过驱动与生物信号表示同步有源感知和意志努力非侵入电疗（肌电图（EMG），脑电图（EEG），眼电（EOG））来促进。要在资源贫乏的设置， 例如 ，在低收入和中等收入国家实现这一目标，我们在场外的现成视频游戏传感器技术利用最新进展提出了一种低成本的人机界面（HMI）。在本文中，我们讨论了低成本的现成的架子传感器具有无创电疗视觉听觉生物反馈，以帮助平衡康复过程中姿势控制集成了开源软件的界面。我们证明对健康志愿者的证明了概念。

图4显示了平稳的追求任务期间的一个身强力壮的性能进行量化提取离线注视眼功能。提取以下特性如表1所示: 特征1 =目标刺激位置和参与者的固定点，当刺激是变化在水平方向上的位置的质心之间的百分比偏差。 特征2 =目标刺激位置和参与者的固定点的?...

Watch this Scientific Journal Video about A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation at JoVE.com

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

A novel low-cost human-machine interface for interactive post-stroke balance rehabilitation system is presented in this article. The system integrates off-the-shelf low-cost sensors towards volitionally driven electrotherapy paradigm. The proof-of-concept software interface is demonstrated on healthy volunteers.

人机界面集成的低成本传感器，具有神经肌肉电刺激系统中风后康复平衡

A stroke is caused when an artery carrying blood from heart to an area in the brain bursts or a clot obstructs the blood flow to brain thereby preventing ...

a-human-machine-interface-integrating-low-cost-sensors-with

Research

JoVE Journal

Neuroscience

10.4K 次观看.  Indian Institute of Technology Gandhinagar. A novel low-cost human-machine interface for interactive post-stroke balance rehabilitation system is presented in this article. The system integrates off-the-shelf low-cost sensors towards volitionally driven electrotherapy paradigm. The proof-of-concept software interface is demonstrated on healthy volunteers.

视频: A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Development of an effective brain-machine-interface (BMI) system for restoration and rehabilitation of bipedal locomotion requires accurate decoding of user's intent. Here we present a novel experimental protocol and data collection technique for simultaneous non-invasive acquisition of neural activity, muscle activity, and whole-body kinematics during various locomotion tasks and conditions.

同时头皮脑电图（EEG），肌电图（EMG）和全身分部惯性录制多模态神经解码

Recent  studies support the involvement of supraspinal networks in control of bipedal  human walking. Part of this evidence  encompasses studies, ...

科研

行为学

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

To enable intuitive operation of powered artificial legs, an interface between user and prosthesis that can recognize the user's movement intent is desired. A novel neural-machine interface (NMI) based on neuromuscular-mechanical fusion developed in our previous study has demonstrated a great potential to accurately identify the intended movement of transfemoral amputees. However, this interface has not yet been integrated with a powered prosthetic leg for true neural control. This study aimed to report (1) a flexible platform to implement and optimize neural control of powered lower limb prosthesis and (2) an experimental setup and protocol to evaluate neural prosthesis control on patients with lower limb amputations. First a platform based on a PC and a visual programming environment were developed to implement the prosthesis control algorithms, including NMI training algorithm, NMI online testing algorithm, and intrinsic control algorithm. To demonstrate the function of this platform, in this study the NMI based on neuromuscular-mechanical fusion was hierarchically integrated with intrinsic control of a prototypical transfemoral prosthesis. One patient with a unilateral transfemoral amputation was recruited to evaluate our implemented neural controller when performing activities, such as standing, level-ground walking, ramp ascent, and ramp descent continuously in the laboratory. A novel experimental setup and protocol were developed in order to test the new prosthesis control safely and efficiently. The presented proof-of-concept platform and experimental setup and protocol could aid the future development and application of neurally-controlled powered artificial legs.

Neural-machine interfaces (NMI) have been developed to identify the user's locomotion mode. These NMIs are potentially useful for neural control of powered artificial legs, but have not been fully demonstrated. This paper presented (1) our designed engineering platform for easy implementation and development of neural control for powered lower limb prostheses and (2) an experimental setup and protocol in a laboratory environment to evaluate neurally-controlled artificial legs on patients with lower limb amputations safely and efficiently.

工程平台和设计一个Neurally控制供电采用经假体与评价实验方案

To enable intuitive operation of powered artificial legs, an interface between user and prosthesis that can recognize the user's movement intent is ...

生物工程

Paradigms of Lower Extremity Electrical Stimulation Training After Spinal Cord Injury

Skeletal muscle atrophy, increased adiposity and reduced physical activity are key changes observed after spinal cord injury (SCI) and are associated with numerous cardiometabolic health consequences. These changes are likely to increase the risk of developing chronic secondary conditions and impact the quality of life in persons with SCI. Surface neuromuscular electrical stimulation evoked resistance training (NMES-RT) was developed as a strategy to attenuate the process of skeletal muscle atrophy, decrease ectopic adiposity, improve insulin sensitivity and enhance mitochondrial capacity. However, NMES-RT is limited to only a single muscle group. Involving multiple muscle groups of the lower extremities may maximize the health benefits of training. Functional electrical stimulation-lower extremity cycling (FES-LEC) allows for the activation of 6 muscle groups, which is likely to evoke greater metabolic and cardiovascular adaptation. Appropriate knowledge of the stimulation parameters is key to maximizing the outcomes of electrical stimulation training in persons with SCI. Adopting strategies for long-term use of NMES-RT and FES-LEC during rehabilitation may maintain the integrity of the musculoskeletal system, a pre-requisite for clinical trials aiming to restore walking after injury. The current manuscript presents a combined protocol using NMES-RT prior to FES-LEC. We hypothesize that muscles conditioned for 12 weeks prior to cycling will be capable of generating greater power, cycle against higher resistance and result in greater adaptation in persons with SCI.

Spinal cord injury is a traumatic medical condition that may result in elevated risks of chronic secondary metabolic disorders. Here, we presented a protocol using surface neuromuscular electrical stimulation-resistance training in conjunction with functional electrical stimulation-lower extremities cycling as a strategy to ameliorate several of these medical problems.

脊髓损伤后下肢电刺激训练的模式

Skeletal muscle atrophy, increased adiposity and reduced physical activity are key changes observed after spinal cord injury (SCI) and are associated with ...

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance

Assessment of reactive balance traditionally imposes some type of perturbation to upright stance or gait followed by measurement of the resultant corrective behavior. These measures include muscle responses, limb movements, ground reaction forces, and even direct neurophysiological measures such as electroencephalography. Using this approach, researchers and clinicians can infer some basic principles regarding how the nervous system controls balance to avoid a fall. One limitation with the way in which these assessments are currently used is that they heavily emphasize reflexive actions without any need to revise automatic postural reactions. Such an exclusive focus on these highly stereotypical reactions would fail to adequately address how we can modify these reactions should the need arise (e.g., avoiding an obstacle with a recovery step). This would appear to be a glaring omission when one considers the enormous complexity of the environments we face daily. Overall, the status quo when evaluating the neural control of balance fails to truly expose how higher brain resources contribute to preventing falls in complex settings. The present protocol offers a way to require suppression of automatic, but inappropriate corrective balance reactions, and force a selection among alternative action choices to successfully recover balance following postural perturbation.

Here we offer a protocol that allows the user to selectively change affordances and/or constraints on movements that are relevant for recovering balance after postural perturbation.

改进的精益和释放技术，强调反应抑制和反应平衡中的动作选择

Assessment of reactive balance traditionally imposes some type of perturbation to upright stance or gait followed by measurement of the resultant ...

Standing Neurophysiological Assessment of Lower Extremity Muscles Post-Stroke

Transcranial magnetic stimulation (TMS) is a common tool used to measure the behavior of motor circuits in healthy and neurologically impaired populations. TMS is used extensively to study motor control and the response to neurorehabilitation of the upper extremities. However, TMS has been less utilized in the study of lower extremity postural and walking-specific motor control. The limited use and the additional methodological challenges of lower extremity TMS assessments have contributed to the lack of consistency in lower extremity TMS procedures within the literature. Inspired by the decreased ability to record lower extremity TMS motor evoked potentials (MEP), this methodological report details steps to enable post-stroke TMS assessments in a standing posture. The standing posture allows for the activation of the neuromuscular system, reflecting a state more akin to the system's state during postural and walking tasks. Using dual-top force plates, we instructed participants to equally distribute their weight between their paretic and non-paretic legs. Visual feedback of the participants' weight distribution was provided. Using image guidance software, we delivered single TMS pulses via a double-cone coil to the participants' lesioned and non-lesioned hemispheres and measured the corticomotor response of the paretic and non-paretic tibialis anterior and soleus muscles. Performing assessments in the standing position increased the TMS response rate and allowed for the use of the lower stimulation intensities compared to the standard sitting/resting position. Utilization of this TMS protocol can provide a common approach to assess the lower extremity corticomotor response post-stroke when the neurorehabilitation of postural and gait impairments are of interest.

This protocol describes the process for performing a neurophysiological assessment of the lower extremity muscles, tibialis anterior and soleus, in a standing position using TMS in people post-stroke. This position provides a greater probability of eliciting a post-stroke TMS response and allows for the use of reduced stimulator power during neurophysiological assessments.

中风后下肢肌肉的站立神经生理学评估

Transcranial magnetic stimulation (TMS) is a common tool used to measure the behavior of motor circuits in healthy and neurologically impaired ...

Home-Based Monitor for Gait and Activity Analysis

Current outcomes in neuromuscular disorder clinical trials include motor function scales, timed tests, and strength measures performed by trained clinical evaluators. These measures are slightly subjective and are performed during a visit to a clinic or hospital and constitute therefore a point assessment. Point assessments can be influenced by daily patient condition or factors such as fatigue, motivation, and intercurrent illness. To enable home-based monitoring of gait and activity, a wearable magneto-inertial sensor (WMIS) has been developed. This device is a movement monitor composed of two very light watch-like sensors and a docking station. Each sensor contains a tri-axial accelerometer, gyroscope, magnetometer, and a barometer that record linear acceleration, angular velocity, the magnetic field of the movement in all directions, and barometric altitude, respectively. The sensors can be worn on the wrist, ankle, or wheelchair to record the subject&#8217;s movements during the day. The docking station enables data uploading and recharging of sensor batteries during the night. Data are analyzed using proprietary algorithms to compute parameters representative of the type and intensity of the performed movement. This WMIS can record a set of digital biomarkers, including cumulative variables, such as total number of meters walked, and descriptive gait variables, such as the percentage of the most rapid or longest stride that represents the top performance of patient over a predefined period of time.

This innovative device uses magneto-inertial sensors to permit gait and activity analysis in uncontrolled environments. Currently in the qualification process as an outcome measure in the European Medical Agency, one of the applications will be to serve as a clinical endpoint in clinical trials in neuromuscular diseases.

基于家庭的盖特和活动分析监视器

Current outcomes in neuromuscular disorder clinical trials include motor function scales, timed tests, and strength measures performed by trained clinical ...

The Muscle Cuff Regenerative Peripheral Nerve Interface for the Amplification of Intact Peripheral Nerve Signals

Robotic exoskeletons have gained recent acclaim within the field of rehabilitative medicine as a promising modality for functional restoration for those individuals with extremity weakness. However, their use remains largely confined to research institutions, frequently operating as a means of static extremity support as motor detection methods remain unreliable. Peripheral nerve interfaces have arisen as a potential solution to this shortcoming; however, due to their inherently small amplitudes, these signals can be difficult to differentiate from background noise, lowering their overall motor detection accuracy. As current interfaces rely on abiotic materials, inherent material breakdown can occur alongside foreign body tissue reaction over time, further impacting their accuracy. The Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was designed to overcome these noted complications. Consisting of a segment of free muscle graft secured circumferentially to an intact peripheral nerve, the construct regenerates and becomes reinnervated by the contained nerve over time. In rats, this construct has demonstrated the ability to amplify a peripheral nerve's motor efferent action potentials up to 100 times the normal value through the generation of compound muscle action potentials (CMAPs). This signal amplification facilitates high accuracy detection of motor intent, potentially enabling reliable utilization of exoskeleton devices.

This manuscript provides an innovative method for developing a biologic peripheral nerve interface termed the Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI). This surgical construct can amplify its associated peripheral nerve's motor efferent signals to facilitate accurate detection of motor intent and the potential control of exoskeleton devices.

肌袖再生周围神经接口，用于放大完整的周围神经信号

Robotic exoskeletons have gained recent acclaim within the field of rehabilitative medicine as a promising modality for functional restoration for those ...

Evaluating Postural Control and Lower-extremity Muscle Activation in Individuals with Chronic Ankle Instability

Computerized dynamic posturography (CDP) is an objective technique for the evaluation of postural stability under static and dynamic conditions and perturbation. CDP is based on the inverted pendulum model that traces the interrelationship between the center of pressure and the center of gravity. CDP can be used to analyze the proportions of vision, proprioception, and vestibular sensation to maintain postural stability. The following characters define chronic ankle instability (CAI): persistent ankle pain, swelling, the feeling of &#8220;giving way,&#8221; and self-reported disability. Postural stability and fibular muscle activation level in individuals with CAI decreased due to lateral ankle ligament complex injuries. Few studies have used CDP to explore the postural stability of individuals with CAI. Studies that investigate postural stability and related muscle activation by using synchronized CDP with surface electromyography are lacking. This CDP protocol includes a sensory organization test (SOT), a motor control test (MCT), and an adaption test (ADT), as well as tests that measure unilateral stance (US) and limit of stability (LOS). The surface electromyography system is synchronized with CDP to collect data on lower limb muscle activation during measurement. This protocol presents a novel approach for evaluating the coordination of the visual, somatosensory, and vestibular systems and related muscle activation to maintain postural stability. Moreover, it provides new insights into the neuromuscular control of individuals with CAI when coping with real complex environments.

Individuals with chronic ankle instability (CAI) exhibit postural control deficiency and delayed muscle activation of lower extremities. Computerized dynamic posturography combined with surface electromyography provides insights into the coordination of the visual, somatosensory, and vestibular systems with muscle activation regulation to maintain postural stability in individuals with CAI.

评估慢性脚踝不稳个体的姿势控制与下肢肌肉活化

Computerized dynamic posturography (CDP) is an objective technique for the evaluation of postural stability under static and dynamic conditions and ...

神经科学

在下肢机器人治疗期间评估 fNIRS 的大脑激活

An Experiment Using Functional Near-Infrared Spectroscopy and Robot-Assisted Multi-Joint Pointing Movements of the Lower Limb

Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown promise in helping stroke patients regain lost motor functions. One potential avenue for increasing the understanding of how motor recovery occurs is to study brain activation during the movements that are targeted by therapy in healthy individuals. Functional Near-Infrared Spectroscopy (fNIRS) has emerged as a promising neuroimaging technique for examining neural underpinnings of motor function. This study aimed to investigate fNIRS neural correlates of complex lower limb movements in healthy subjects. Participants were asked to perform cycles of rest and movement for 6 min using a robotic device for motor rehabilitation. The task required coordinated knee and ankle joint movements to point to targets displayed on a computer screen. Two experimental conditions with different levels of movement assistance provided by the robot were explored. The results showed that the fNIRS protocol effectively detected brain regions associated with motor control during the task. Notably, all subjects exhibited greater activation in the contralateral premotor area during the no-assistance condition compared to the assisted condition. In conclusion, fNIRS appears to be a valuable approach for detecting changes in oxyhemoglobin concentration associated with multi-joint pointing movements of the lower limb. This research might contribute to the understanding of stroke motor recovery mechanisms and might pave the way for improved rehabilitation treatments for stroke patients. However, further research is needed to fully elucidate the potential of fNIRS in studying motor function and its applications in clinical settings.

作者聚焦：使用 fNIRS 评估机器人辅助下肢康复中的大脑活动

It is estimated that 1 in 6 individuals worldwide will have a stroke in their lifetime, causing long-term disability, whose rehabilitation mechanisms are still poorly understood. This study proposes a protocol to evaluate brain activation by functional near-infrared spectroscopy (fNIRS) during a lower limb robotic therapy session.

使用功能性近红外光谱和机器人辅助下肢多关节指向运动的实验

Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown promise ...

人机界面集成的低成本传感器，具有神经肌肉电刺激系统中风后康复平衡

摘要

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此视频中的章节

同时头皮脑电图（EEG），肌电图（EMG）和全身分部惯性录制多模态神经解码

工程平台和设计一个Neurally控制供电采用经假体与评价实验方案

脊髓损伤后下肢电刺激训练的模式

改进的精益和释放技术，强调反应抑制和反应平衡中的动作选择

中风后下肢肌肉的站立神经生理学评估

基于家庭的盖特和活动分析监视器

肌袖再生周围神经接口，用于放大完整的周围神经信号

评估慢性脚踝不稳个体的姿势控制与下肢肌肉活化

使用功能性近红外光谱和机器人辅助下肢多关节指向运动的实验

使用功能性近红外光谱和机器人辅助下肢多关节指向运动的实验