这项工作是由美国国立卫生研究院资助P20 GM109098，NSF和西弗吉尼亚大学ADVANCE赞助计划（VG）和西弗吉尼亚大学部门启动资金支持。

参与实验的所有参与者都经过批准的西弗吉尼亚大学的机构审查委员会（IRB）知情同意程序。 1.整体系统性能，设计，和一般的实验任务注意:完整的安装是由以下几部分组成:EMG设备和相关的数字采集（DAQ）设备;运动捕捉系统（该协议包含了一个积极的LED系统）;与图-的八个线圈和立体定位设备TMS单元;一个虚拟现实的耳机和相关的电脑和软件;和一个自定义同步电路。 图1示意性概述了协议组件之间的连接性。 <ol><li>系统组件的连接<ol><li>连接肌电图前置放大器主放大器。 </li><li>肌电图连接放大器的输出到数据采集记录使用BNC或类似的CONNEC设备输入块系统蒸发散。 </li><li>数据采集​​录音设备连接到专用电脑，将执行一个数据采集脚本（补充文件）。 </li><li> VR控制计算机的并行输出连接到定制电路单元（见下节）。 </li><li>连接同步和动作捕捉触发的定制电路输出沿着肌电信号连接数据采集记录块。 </li><li>拆分动作捕捉触发，并将其连接到肌电图数据采集设备的"模拟输入启动"端口，以及控制动作捕捉设备计算机上的触发连接。 注:所描述的设备（动作捕捉和EMG）各自的数据采集流的开始之间的时间差的范围可以从160〜190毫秒。这个时间差动机在这个协议中所描述的同步电路的设计和可能是由这两个系统之间的软件和硬件差异而引起的。 </li> &lt;LI&gt;连接TMS触发定制电路单元口BNC输入触发TMS控制单元。 </li><li>建立使用供应商提供的软件和物理网络连接的VR和动作捕捉的计算机之间的网络连接。 </li><li>虚拟现实耳机连接到VR计算机，并确保可操作性与任何脚本/中显示的虚拟环境来参加节目。 </li></ol></li></ol><img alt="图1" src="/files/ftp_upload/52906/52906fig1.jpg" /> 图1:整个安装的连接此布局的描述了我们系统的元件之间的一般连通性。同步电路在其它地方更详细的描述在文本。蓝色曲线对应这会启动动作捕捉和肌电图的数据流信号。此事件是使用在此协议中描述的设备高达190毫秒的时间延迟的来源。红色曲线对应VR发起synchronizat即伴随的动作捕捉和肌电图系统记录并随后用于相应数据流的时间对准离子事件。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52906/52906fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 系统集成与同步2.一般详情注:单独的数据采集系统中的这个协议（运动捕捉和EMG）的同步是通过使用的事件信号是共同的所有记录数据流来实现的。使用一个共同的情况下，所有的信号都可以暂时重新调整后的数据收集（使用设备在本协议中向上的190毫秒）减少实时记录不符。在这个协议中，公用信号从VR系统并行端口信号起源。共用信号被路由到一个电路，其允许单独的数据的同步流通过直接记录与肌电信号，并同时关闭动作捕捉LED。该电路采用基本的工具和技术构建的电子元件构成，类似于电路别处9描述。 <ol><li>设计，布局和同步电路的构建<ol><li>确定对设备的控制单元中的任何模拟基于TTL的触发机制（ 如 TMS，动作捕捉）和熟悉的触发要求，如TTL脉冲方向（正极/负极）和幅度。模拟触发机制往往具有共同的"BNC"同轴连接器，使连接组件简单。 </li><li>增加一个额外的LED到运动捕捉系统要用于信号同步;路线通过同步电路LED的布线（ 图3）。 </li><li>确定电气元件的参数（ 如电阻，电容），以TUR需要n关闭同步LED为一个特定的时间量。发现的时间，电路的同步LED由等式关闭量:吨= 1.1 * R1 * C1中。这个时间被认为是小于一个实验运动的平均持续时间。例如，目前所描述的实验所需要的电阻和电容额定大约一兆欧姆，一个微法拉，分别。 </li><li>使用电烙铁附着电气元件到印刷"原型制造"或"项目"的电路板下面的图 3中所示的示意性括该电路中一个常用的塑料"项目"框。它可能会需要钻孔在此框中的BNC连接器。该电路可以容易地通过5伏的USB电源从桌面计算机来供电;将有必要来解构USB电缆将隔离电源和地线。旁路电容也可能需要调节功率至555芯片（ 图 3中未示出）。 </li><li>检查用电路基板电部件之间的任何意外的锡桥。如果找到，删除焊料一吸尘工具或加热焊接和机械去除桥接连接。 </li></ol></li></ol><img alt="图2" src="/files/ftp_upload/52906/52906fig2.jpg" /> 图2:试验流程图。该流程图概括了典型的实验试验，其中包括，TMS刺激过程中发生的刺激和信号事件。在整个试验中发生的并行端口代码显示在DB25原理图符号（浅蓝色）。 <ol start="2"><li>同步详细信息<ol><li>使用类似的流程图图 2，确定何时单个设备应的实验运动的过程中被触发。例如，一些设备可以单独触发，而另一些可以同时触发。 </l我&gt; <li>在那些需要触发或信号（ 如蓝并行端口符号， 图2）的时间点，确定哪个并行端口信号线使用，并将其纳入了VR系统。这是通过在运动过程中发送数值到并行端口在指定的时间，表示一个二进制数字的每一行来实现的。有关并行端口的基于信令的详细信息，请参考讨论。 </li></ol></li></ol><img alt="图3" src="/files/ftp_upload/52906/52906fig3.jpg" /> 图3:同步电路，该示意图显示我们的自定义同步电路的布局。 NAND门的默认输出是高电压状态;这个电压输出被发送到通过该同步LED的电路路由的晶体管的栅极。此默认状态下使电路闭合，它保持在点亮状态的LED指示灯。在接收到同步trigge器R并联端口信号（红色迹线在插图），555装置的内部状态被翻转呈现输出到高状态时，切断该LED（蓝色迹线）。如果发生这种情况，在C1上（绿色迹线）上的电压逐渐达到该复位555的内部状态，重新激活该LED的电压。并行端口的同步触发信号也被直接路由到连接到TMS输入触发端口一BNC连接器。注意:该触发信号的方向可具有被逆转（从​​正性至负向或反之亦然）根据研究者的特定设备的要求。加入这个触发器输出会很容易地完成这项任务的"逆变器"芯片。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52906/52906fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 3.实验方法<ol><li>安全程序和知情同意<ol><li> Ensu再次，所有的实验程序由机构审查委员会（IRB）的批准。解释所有的程序的参与者，并获得知情同意与IRB批准文件。 </li><li>获得知情同意后，从事与参与者一个基本TMS的安全检查，以确保它们不会有耳鸣，癫痫症或癫痫发作，或其他条件癫痫较高风险的家族史。 </li><li>在TMS刺激，严格要求使用防护耳塞，以防止听力受损。 </li></ol></li><li>肌电采集<ol><li>根据读者的研究的科学目标，确定从哪个手臂肌肉记录肌电信号。对于本协议所述的研究，扭矩在肩部产生和运动过程中肘关节进行了调查。因此，EMG信号记录分别从主要浅表肌肉作用在这两个关节，如三角肌，胸肌，二头肌，三头肌，和brachioradialis。 </li><li>做出各种肌电设备包括放大器，前置放大器，传感器线，和传感垫根据制造商的规格通过连接匹配连接器之间的所有必要的电连接。 </li><li>通过轻轻用醇棉签清洗它，除去任何过量的毛发用剃刀，并通过施加一个轻微的磨蚀凝胶制备各电极的网站。适当的整地将确保一致的和低电极对皮肤阻抗值（&lt;10千欧）和记录EMG信号的高信噪比。 </li><li>有主题进行设计，可以隔离基于公认的解剖和生物力学描述10个人感兴趣的肌肉等长收缩。例如，以隔离二头肌，要求参与者抗蚀肘关节强加延伸。 </li><li>有后受试者进行肌肉收缩隔离，贴上差双极肌电电极在厚，中央PORTI上，或者在接受位置11"肚"每一块肌肉的。这确保了肌纤维的最大数量的覆盖面和周边肌肉的减少"串扰"。一定要调整双极电极&#39;最长轴线沿肌肉，平行于纤维。 </li><li>贴上根据设备规格的肌电接地电极（ 如皮肤上的C7椎体）。 </li><li>记录通过数据采集设备通过自定义的计算机脚本控制放大的肌电信号。在当前的协议中使用的脚本被附加作为补充文件。 </li><li>调整通过移动转盘上的肌电图前置放大器适用于记录信号所需的水平的收益。避免导致记​​录的信号超出录音设备（一般为5V）的输入范围增益值。常见的EMG增益值是1000-4000之间。 </li><li>执行类似的等长收缩的那些步骤3.2.4进行目视检查肌电图西尼亚ls以确保它们的高质量（即高信噪比）。重新定位的电极并在必要时改变信号增益。 </li></ol></li><li>运动捕捉系统准备<ol><li>校准使用根据制造商的说明供应商提供的指令和设备的运动跟踪摄像机。 </li><li>用胶带等包装材料，附着活性的LED传感器附近的臂和在生物力学模型的构建中使用其它感兴趣的解剖点的关节骨性标志:在手腕上的食指，径向和尺骨茎突远端指骨，肩，胸锁槽，剑突和C7棘突的肘部，喙突和肩峰过程鹰嘴过程。附加其他LED到VR耳机来设定视点在虚拟环境中。 </li><li>连接每个LED到被附连到无线驱动器单元的布线线束。打开驱动程序未并确保所有LED的正常照明。 </li><li>放置同步在方便的位置远离主体的LED，但在相机的明确的说法。 </li></ol></li><li>经颅磁刺激脑立体定位<ol><li>校准的硬件和软件设计的TMS登记12，以允许精确线圈放置。这通常涉及共同注册TMS线圈与解剖标志，如鼻根，耳前点和鼻尖。一个参与者和激励线圈之间的立体登记是不可或缺的一致刺激的定位。 </li></ol></li><li> MEP热点本地化和环保部门限Pprocedures <ol><li>执行所谓的"热点"的技术来定位皮层TMS-敏感区域产生最大振幅的MEP与刺激后8,13,14最低阈值。经颅磁刺激研究电机系统通常涉及刺激，其控制在一个特定身体部分的运动皮层区域 （例如手臂和手）15。 </li><li>记录对参与者的头皮与校准立体登记设备和相关软件的任何理想的刺激点的位置。在每个位置记录的软件，确保其准确性搬迁现场，并再次刺激，寻找类似的MEP的反应。 </li></ol></li><li>在虚拟现实行为的任务<ol><li>设计的行为的任务（例如，达到运动）的实验中所使用的参数。在目前的研究中，任务是达到在不同空间位置顺序设置虚拟目标。的目标的大小定义了与其中与会者移动的准确性。这样的设计，改变的方向和关节力矩大小是诱发参与者达到了目标的运动。 </li><li>设置的虚拟现实环境，指导通过使用商业VR软件，根据制造商的协议是与耳机和运动跟踪系统兼容的行为的任务受试者。熟悉该软件包的所需的计算资源和编程语言的要求。常见的VR软件包与语言包括Python，C ++，C＃，和其他人进行编程的能力。另外，通过并行端口，用于同步程序模拟输出和感兴趣的特定事件的标记（ 图2）。在目前的实验中，在VR软件输出处的​​任务的每个重复的开始和在所需的TMS刺激次事件。 </li><li>连接VR输出给同步电路（图3）和/或使用的电缆具有匹配连接器的要同步的其他设备。 </li><li>指导患者进行VR行为的任务。在目前的研究中，虚拟现实环境是提出使用头戴式显示器，参与者观看的球形目标阵列。利用虚拟现实软件，通过改变目标（颜色， 位置等）的出现特定程序的移动序列和参与者熟悉这些操作。另外告知任何其他希望的运动约束的参与者。例如，参加者在目前的研究提出，以保持所有臂段内移动的垂直平面内，而达到为目标。 </li><li>一旦参与者习惯于实验动作，记录肌电图和动作捕捉数据，并同步使用自定义脚本或供应商提供的软件包的信号。调整每个数据采集系统，以所需的值的采样率;此外熟悉和适应任何制造商特定的参数，如运动跟踪LED亮度。 </li></ol></li></ol>

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The authors have no conflicts of interest to declare.

本文的目的是描述了一种用于掺入VR到人体运动的研究和用于同步各个数据流的方法。虚拟现实将扩大研究人员试图再现真实世界的运动的场景在实验室环境的能力。结合VR与其他神经肌肉记录和刺激方法，形成一套强大的工具，为全面研究人类运动控制机制。在精心设计的实验中获得由此产生的多维数据集可以加深我们运动的神经控制的理解。 之一的本系统的更重要的特征是，与普通的VR生成的事件进行同步的电生理和运动捕捉数据流的能力。在本协议中所描述的定制电路作为一个灵活的，具有成本效益的基础，可以被改变，以满足其他EXP的独特需求erimental范式和设备，在其他领域的9类似的解决方案。公共同步事件是源自，经营我们的虚拟现实软件的计算机的并行输出命令。一个标准的并行接口的优点是它的简单，速度和灵活性。内并行接口有八个独立的数据线，每一个代表从2 0的二进制数到2 7;这些数字的总和可以等于数字范围从0到255的每个相应的数据线的可以用作单独的和同时的触发信号与众多系统接口。这些触发信号通常是简单的方波电压信号，通常被称为TTL信号或脉冲。 期间的移动试验中，公用同步事件是基于一个与会者的位置在虚拟环境中发起跟踪使用红外基于LED的运动捕捉系统。同步从我们的VR软件事件信号（TTL）被路由到其目的是在VR同步事件同时发送到我们的肌电图数据和动作捕捉流（ 图3）的定制电路。肌电图系统记录的TTL脉冲持续的肌肉活动。在VR信号通过电路，它控制着电源以从运动捕获系统的LED的活性部分也被路由。在接收到TTL脉冲，重新路由LED熄灭的时间短的时间。此事件记录的动作捕捉系统，是时间上同步与记录的肌电图系统的TTL脉冲。这个事件可以随后用于对准信号进行分析。 电路（图3中示意性示出）的有效部分主要是基于一个专用集成电路（IC）或"芯片"，通常被称为"555定时器电路"16。 555的输出定时电路（通常是低电压）进入一NAND（否定而）门连同由USB功率提供一个恒定电压。阿非门是输出一个低的值（即0V）当两个输入都是高电平（例如干线电压）的电逻辑部件。在接收一个同步事件信号在图3中的插图详细我们电路的操作。该电路关闭该LED的持续时间取决于用于R1和C1的值，并且由等式发现:吨= 1.1 * R1 * C1中。之一兆欧和一个微法拉的当前描述的所需试验电阻和电容值，分别产生同步光静止比典型的运动（大约一秒钟本设计）的持续时间短。 目前的协议的同步方法比市售的选项很多好处。电路元件和必要的工具，它是一个ssembly很容易在电子元件供应商的最低成本9。此外，同步一个简单的基于硬件的解决方案，可以让实验者更容易调试实验过程中可能会出现的问题。最后，通过使用相当普遍TTL信号，可以很容易地适应，利用不同的方法和设备（如EEG）新的实验设计。在这个协议中所描述的多功能系统的一个潜在的缺点是在实验装置与众多的数据收集系统的复杂性。这可能会导致长期实验会议，参加者的疲劳，并为系统故障多的机会。实验者可以最大限度地减少通过设计简洁的实验范式，旨在探讨非常具体的神经肌肉现象的问题。 在这个协议的目的是提供普及区实现的电路和整体同步过程idelines用于进行生物力学实验与多个，同时记录数据流。本协议描述的程序从与模拟输入或触发或LED信号的任何设备同步数据流。但是，使用被动式运动跟踪系统，而LED的研究人员，将有可能改变目前所描述的解决方案。系统的被动运动捕捉和其他记录，并经过数字触发将不需要依靠同步电路拉动设备。相反，这些系统将依靠定制软件为基础的解决方案，它的设计可从当前系统的示例来推断。因此，该协议提供可推广的原则，以协助其他独特的方案设计的解决方案。

虚拟现实（VR）正迅速成为一个可访问研究工具用于许多领域，包括人体运动的研究。上肢运动的研究，特别是通过将VR受益。虚拟现实允许旨在探讨手臂运动控制的具体运动学和动力学特性实验参数的快速定制。这些参数可以单独调整每个主题。例如，虚拟目标的位置可以进行调整以确保在受试者相同的初始臂姿势。虚拟现实也让视觉反馈过程中的实验操作，这在visuomotor研究1的宝贵工具- 5。 利用逼真的虚拟现实环境中与其他生物力学工具也将允许自然的运动场景中，以测试运动模式。这种布置变得越来越有价值的学习和以后的疾病和伤害6,7康复练习。模仿自然的动作和环境 （例如执行在虚拟厨房运动）在临床环境将使康复专家能够更精确地描述个体的损伤在现实世界环境。高度个性化的障碍的描述将允许更集中的治疗策略，潜在地增加的功效和减少重建的持续时间。 结合虚拟现实与其他工具，如经颅磁刺激（TMS），表面肌电图（EMG）和全身动作捕捉，创建了一个非常强大和灵活的平台，学习运动在人类神经肌肉控制。经颅磁刺激是测量降电机途径的兴奋性和功能完整性的一个功能强大的非侵入性方法（例如皮质脊髓束）通过肌电responsES如运动诱发电位（MEPS）8。现代三维运动捕捉系统还使研究人员一起研究神经肌肉活性，产生的运动运动学和动力学。这允许创建的肌肉骨骼系统的极其细致模型以及假设关于神经控制器的结构和功能的测试。这些研究将扩大我们的科学的人体感觉系统的知识，导致改善治疗肌肉骨骼和神经系统疾病。 然而，随着多功能系统的一个主要问题是分开记录的数据流（例如，运动捕捉，肌电图等 ）的同步。该协议的目的是描述常见市售系统的一般化结构运动期间同时记录生物力学和生理测量。使用的设备，从其他调查不同的厂家可能要改变这个协议的内容，以满足他们的特定需求。然而，从该协议的一般原则仍然应该适用。

<table><tbody><tr><td>Transcranial magnetic stimulator</td><td>Magstim</td><td>N/A</td><td>TMS stimulator and coils</td></tr><tr><td>Impulse X2</td><td>PhaseSpace</td><td>N/A</td><td>Motion capture system</td></tr><tr><td>MA300 Advanced Multi-Channel EMG System</td><td>Motion Lab Systems</td><td>MA300-28</td><td>EMG pre-amplifier and amplifier</td></tr><tr><td>Norotrode EMG electrodes</td><td>Myotronics</td><td>N/A</td><td>EMG electrodes</td></tr><tr><td>BNC-2111 Single-Ended, Shielded BNC Connector Block</td><td>National Instruments</td><td>779347-01</td><td>BNC Connector Block</td></tr><tr><td>NI PXI-1033&lt;br/&gt; 5-Slot PXI Chassis with Integrated MXI-Express Controller</td><td>National Instruments</td><td>779757-01</td><td>DAQ chassis</td></tr><tr><td>NI PXI-6254&lt;br/&gt; 16-Bit, 1 MS/s (Multichannel), 1.25 MS/s (1-Channel), 32 Analog Inputs</td><td>National Instruments</td><td>779118-01</td><td>DAQ card</td></tr><tr><td>SHC68-68-EPM Cable (2m)</td><td>National Instruments</td><td>192061-02</td><td>Shielded cable</td></tr><tr><td>DK1 or DK2</td><td>Oculus VR</td><td>N/A</td><td>Ocuclus Rift headset</td></tr><tr><td>Vizard 5 Lite</td><td>WorldViz</td><td>N/A</td><td>Virtual reality software</td></tr><tr><td>C1 and C2 capacitors</td><td>varied</td><td>N/A</td><td>Adjust values to suit</td></tr><tr><td>R1 and R2 resistors</td><td>varied</td><td>N/A</td><td>Adjust values to suit</td></tr><tr><td>CD4011 NAND gate</td><td>varied</td><td>N/A</td><td>NAND gate</td></tr><tr><td>2N2222 transistor</td><td>varied</td><td>N/A</td><td>Transistor</td></tr><tr><td>NE555 timer circuit</td><td>varied</td><td>N/A</td><td>Timer circuit</td></tr><tr><td>DB25 and USB connectors</td><td>varied</td><td>N/A</td><td>parallel and USB connectors</td></tr></tbody></table>

multifunctional setup for studying human motor control using transcranial magnetic stimulation, electromyography, motion capture, and virtual reality

运动在人类神经肌肉控制的研究与实现的众多技术。非侵入性的方法考察神经肌肉功能包括经颅磁刺激，肌电图，和三维运动捕捉。的现成的和具有成本效益的虚拟现实的解决方案的出现在再现"现实世界"的环境和动作在实验室设置扩大研究人员的能力。自然主义运动的分析，不仅争取电机控制在健康人更深入的了解，而且还允许实验和针对特定运动障碍（ 如中风）康复战略。这些工具的组合使用会导致电机控制的神经机制越来越深入的了解。当组合这些数据采集系统的一个关键要求是各个数据流之间的精细时间的对应关系。 Ť他的协议描述了一个多功能系统的总体连通性，系统间的信令，以及记录的数据的时间同步。组件系统的同步是通过使用一个可定制电路，与现成的部件和最少的电子组装技能容易地做出的，主要完成。

在这个设置中，众多的数据流的同步允许一个记录上肢的移动过程中发生的运动学，连续肌肉活动（肌电图），和瞬时神经肌肉活动（MEPS）。一个给定的动作重复试验，需要在整个运动重建MEP响应曲线图从一个采集的4显示数据为准。 图4A显示了相应的同步信号和事件审单过程中的这些数据流的一个例子。相对于所述同步事件的信号的时间对准是用信号分析软件（信号使用的是同步事件作为共同颞锚"移"在时间上）的简单事后过程。然后信号可以是时间归由每个运动试验的持续时间。如果不同步，肌电图和动作捕捉数据流可以有时间出入克吃160-190毫秒。然而，通过利用除同步到广泛使用的TTL信号，用户应该期望以最小化数据流之间的时间误差，以它们的信号（在该例子大约一毫秒）的采样频率的极限。 图4B示出平均角速度运动学和动力学在24个试验为单一的运动，从试验而不TMS二头肌肌电轮廓的长头中同样的动作，以及从与单脉冲TMS的试验运动期间，相应的重构的MEP型材到相同的目标。 <img alt="图4" src="/files/ftp_upload/52906/52906fig4.jpg" /> 图4:肌电图和运动捕捉对齐的实验试验过程中记录（A）代表性的信号显示在图表的左边的列。蓝色和红色圆圈对应于记录由两个分隔符同一VR生成的同步事件Ë件装备（通过将黑线所示）。这些时间点和各自的数据是使用定制软件购买时间对准。这两个时间点之间的差可以是向上的使用在这个协议中所描述的设备在使用190毫秒;使用不同的设备其他研究者可能会遇到不同的延迟。 （二）时间的调整后，场均可以创建数据来描述的生理，运动和运动的动态特性。这些数据代表在同一​​运动中的24试验;在二头肌的MEP图形的酒吧和其它图的阴影部分表示标准偏差。这些数据随后可以用来描述电位降电机控制信号相对于肌肉活动和运动运动学和动力学。

Watch this Scientific Journal Video about Multifunctional Setup for Studying Human Motor Control Using Transcranial Magnetic Stimulation, Electromyography, Motion Capture, and Virtual Reality at JoVE.

Multifunctional Setup for Studying Human Motor Control Using Transcranial Magnetic Stimulation, Electromyography, Motion Capture, and Virtual Reality

Transcranial magnetic stimulation, electromyography, and 3D motion capture are commonly used non-invasive techniques for investigating neuromuscular function in humans. In this paper, we describe a protocol that synchronously samples data generated by all three of these tools along with the unique addition of virtual reality stimulus presentation and feedback.

多功能设置研究人类电机控制用经颅磁刺激，肌电图，运动捕捉和虚拟现实

The study of neuromuscular control of movement in humans is accomplished with numerous technologies. Non-invasive methods for investigating neuromuscular ...

multifunctional-setup-for-studying-human-motor-control-using

Nanyang Technological University

Research

JoVE Journal

Behavior

10.8K 次观看.  West Virginia University. Transcranial magnetic stimulation, electromyography, and 3D motion capture are commonly used non-invasive techniques for investigating neuromuscular function in humans. In this paper, we describe a protocol that synchronously samples data generated by all three of these tools along with the unique addition of virtual reality stimulus presentation and feedback.

视频: Multifunctional Setup for Studying Human Motor Control Using Transcranial Magnetic Stimulation, Electromyography, Motion Capture, and Virtual Reality

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

Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks

There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is relatively flexible with respect to participant positioning and allows for some head movements during tasks. Additionally, it is inexpensive, light weight, and portable, with very few contraindications to its use. This presents a unique opportunity to study functional brain activity during motor tasks in individuals who are typically developing, as well as those with movement disorders, such as cerebral palsy. An additional consideration when studying movement disorders, however, is the quality of actual movements performed and the potential for additional, unintended movements. Therefore, concurrent monitoring of both blood flow changes in the brain and actual movements of the body during testing is required for appropriate interpretation of fNIRS results. Here, we show a protocol for the combination of fNIRS with muscle and kinematic monitoring during motor tasks. We explore gait, a unilateral multi-joint movement (cycling), and two unilateral single-joint movements (isolated ankle dorsiflexion, and isolated hand squeezing). The techniques presented can be useful in studying both typical and atypical motor control, and can be modified to investigate a broad range of tasks and scientific questions.

Monitoring brain activity during upright motor tasks is of great value when investigating the neural source of movement disorders. Here, we demonstrate a protocol that combines functional near infrared spectroscopy with continuous monitoring of muscle and kinematic activity during 4 types of motor tasks.

感觉和运动脑区与运动同步和肌电图监测功能近红外光谱在运动任务

There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is ...

Utilizing Transcranial Magnetic Stimulation to Study the Human Neuromuscular System

Transcranial magnetic stimulation (TMS) has been in use for more than 20 years 1, and has grown exponentially in popularity over the past decade. While the use of TMS has expanded to the study of many systems and processes during this time, the original application and perhaps one of the most common uses of TMS involves studying the physiology, plasticity and function of the human neuromuscular system. Single pulse TMS applied to the motor cortex excites pyramidal neurons transsynaptically 2 (Figure 1) and results in a measurable electromyographic response that can be used to study and evaluate the integrity and excitability of the corticospinal tract in humans 3. Additionally, recent advances in magnetic stimulation now allows for partitioning of cortical versus spinal excitability 4,5. For example, paired-pulse TMS can be used to assess intracortical facilitatory and inhibitory properties by combining a conditioning stimulus and a test stimulus at different interstimulus intervals 3,4,6-8. In this video article we will demonstrate the methodological and technical aspects of these techniques. Specifically, we will demonstrate single-pulse and paired-pulse TMS techniques as applied to the flexor carpi radialis (FCR) muscle as well as the erector spinae (ES) musculature. Our laboratory studies the FCR muscle as it is of interest to our research on the effects of wrist-hand cast immobilization on reduced muscle performance6,9, and we study the ES muscles due to these muscles clinical relevance as it relates to low back pain8. With this stated, we should note that TMS has been used to study many muscles of the hand, arm and legs, and should iterate that our demonstrations in the FCR and ES muscle groups are only selected examples of TMS being used to study the human neuromuscular system.

Transcranial magnetic stimulation (TMS) is a non-invasive tool to gain insight on the physiology and function of the human nervous system. Here, we present our TMS techniques to study cortical excitability of the upper limb and lumbar musculature.

利用经颅磁刺激，以研究人类的神经肌肉系统

Transcranial magnetic stimulation (TMS) has been in use for more than 20 years 1, and has grown exponentially in popularity over the past decade.  While ...

医学

Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics

Transcranial magnetic stimulation techniques allow for an in-depth investigation into the neural mechanisms that underpin human behavior. To date, the use of TMS to study human movement, has been limited by the challenges related to precisely timing the delivery of TMS to features of the unfolding movement and, also, by accurately characterizing kinematics and kinetics. To overcome these technical challenges, TMS delivery and acquisition systems should be integrated with an online motion tracking system. The present manuscript details technical innovations that integrate multiple acquisition systems to facilitate and advance the use of TMS to study human movement. Using commercially available software and hardware systems, a step-by-step approach to both the hardware assembly and the software scripts necessary to perform TMS studies triggered by specific features of a movement is provided. The approach is focused on the study of upper limb, planar, multi-joint reaching movements. However, the same integrative system is amenable to a multitude of sophisticated studies of human motor control.

The use of transcranial magnetic stimulation (TMS) to study human motor control requires the integration of data acquisition systems to control TMS delivery and simultaneously record human behavior. The present manuscript provides a detailed methodology for integrating data acquisition systems for the purpose of investigating human movement via TMS.

合并多个数据采集系统来研究皮质输出和多段生物力学

Transcranial magnetic stimulation techniques allow for an in-depth investigation into the neural mechanisms that underpin human behavior. To date, the use ...

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation

The effect of a stimulus to the brain depends not only on the parameters of the stimulus but also on the dynamics of brain activity at the time of the stimulation. The combination of electroencephalography (EEG) and transcranial magnetic stimulation (TMS) in a real-time brain state-dependent stimulation system allows the study of relations of dynamics of brain activity, cortical excitability, and plasticity induction. Here, we demonstrate a newly developed method to synchronize the timing of brain stimulation with the phase of ongoing EEG oscillations using a real-time data analysis system. This real-time EEG-triggered TMS of the human motor cortex, when TMS is synchronized with the surface EEG negative peak of the sensorimotor &#181;-alpha (8-14 Hz) rhythm, has shown differential corticospinal excitability and plasticity effects. The utilization of this method suggests that real-time information about the instantaneous brain state can be used for efficacious plasticity induction. Additionally, this approach enables personalized EEG-synchronized brain stimulation which may lead to the development of more effective therapeutic brain stimulation protocols.

This paper describes real-time electroencephalography-triggered transcranial magnetic stimulation to study and modulate human brain networks.

脑状态依赖性脑刺激与实时脑脑图触发颅内磁刺激

The effect of a stimulus to the brain depends not only on the parameters of the stimulus but also on the dynamics of brain activity at the time of the ...

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

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 delivery of oxygen and nutrients. About half of the stroke survivors are left with some degree of disability. Innovative methodologies for restorative neurorehabilitation are urgently required to reduce long-term disability. The ability of the nervous system to reorganize its structure, function and connections as a response to intrinsic or extrinsic stimuli is called neuroplasticity. Neuroplasticity is involved in post-stroke functional disturbances, but also in rehabilitation. Beneficial neuroplastic changes may be facilitated with non-invasive electrotherapy, such as neuromuscular electrical stimulation (NMES) and sensory electrical stimulation (SES). NMES involves coordinated electrical stimulation of motor nerves and muscles to activate them with continuous short pulses of electrical current while SES involves stimulation of sensory nerves with electrical current resulting in sensations that vary from barely perceivable to highly unpleasant. Here, active cortical participation in rehabilitation procedures may be facilitated by driving the non-invasive electrotherapy with biosignals (electromyogram (EMG), electroencephalogram (EEG), electrooculogram (EOG)) that represent simultaneous active perception and volitional effort. To achieve this in a resource-poor setting, e.g., in low- and middle-income countries, we present a low-cost human-machine-interface (HMI) by leveraging recent advances in off-the-shelf video game sensor technology. In this paper, we discuss the open-source software interface that integrates low-cost off-the-shelf sensors for visual-auditory biofeedback with non-invasive electrotherapy to assist postural control during balance rehabilitation. We demonstrate the proof-of-concept on healthy volunteers.

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 ...

神经科学

集成 VR 和生物传感器进行定量运动肌肉活动评估

Setup for the Quantitative Assessment of Motion and Muscle Activity During a Virtual Modified Box and Block Test

The ability to move allows us to interact with the world. When this ability is impaired, it can significantly reduce one's quality of life and independence and may lead to complications. The importance of remote patient evaluation and rehabilitation has recently grown due to limited access to in-person services. For example, the COVID-19 pandemic unexpectedly resulted in strict regulations, reducing access to non-emergent healthcare services. Additionally, remote care offers an opportunity to address healthcare disparities in rural, underserved, and low-income areas where access to services remains limited. 
Improving accessibility through remote care options would limit the number of hospital or specialist visits and render routine care more affordable. Finally, the use of readily available commercial consumer electronics for at-home care can enhance patient outcomes due to improved quantitative observation of symptoms, treatment efficacy, and therapy dosage. While remote care is a promising means to address these issues, there is a crucial need to quantitatively characterize motor impairment for such applications. The following protocol seeks to address this knowledge gap to enable clinicians and researchers to obtain high-resolution data on complex movement and underlying muscle activity. The ultimate goal is to develop a protocol for remote administration of functional clinical tests. 
Here, participants were instructed to perform a medically-inspired Box and Block task (BBT), which is frequently used to assess hand function. This task requires subjects to transport standardized cubes between two compartments separated by a barrier. We implemented a modified BBT in virtual reality to demonstrate the potential of developing remote assessment protocols. Muscle activation was captured for each subject using surface electromyography. This protocol allowed for the acquisition of high-quality data to better characterize movement impairment in a detailed and quantitative manner. Ultimately, these data have the potential to be used to develop protocols for virtual rehabilitation and remote patient monitoring.

作者聚焦:利用虚拟现实和肌电图增强远程康复

The protocol described here aims to enhance the quantitative evaluation of upper limb deficits, with the goal of developing additional technology for remote assessment both in the clinic and at home. Virtual reality and biosensor technologies are combined with standard clinical techniques to provide insights into the functioning of the neuromuscular system.

用于在虚拟改良的 Box and Block 测试期间定量评估运动和肌肉活动的设置

The ability to move allows us to interact with the world. When this ability is impaired, it can significantly reduce one's quality of life and ...

工程学

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain

Mapping the motor cortex with transcranial magnetic stimulation (TMS) has potential to interrogate motor cortex physiology and plasticity but carries unique challenges in children. Similarly, transcranial direct current stimulation (tDCS) can improve motor learning in adults but has only recently been applied to children. The use of tDCS and emerging techniques like high&#8211;definition tDCS (HD-tDCS) require special methodological considerations in the developing brain. Robotic TMS motor mapping may confer unique advantages for mapping, particularly in the developing brain. Here, we aim to provide a practical, standardized approach for two integrated methods capable of simultaneously exploring motor cortex modulation and motor maps in children. First, we describe a protocol for robotic TMS motor mapping. Individualized, MRI-navigated 12x12 grids centered on the motor cortex guide a robot to administer single-pulse TMS. Mean motor evoked potential (MEP) amplitudes per grid point are used to generate 3D motor maps of individual hand muscles with outcomes including map area, volume, and center of gravity. Tools to measure safety and tolerability of both methods are also included. Second, we describe the application of both tDCS and HD-tDCS to modulate the motor cortex and motor learning. An experimental training paradigm and sample results are described. These methods will advance the application of non-invasive brain stimulation in children.

We demonstrate protocols for the modulation (tDCS, HD-tDCS) and mapping (robotic TMS) of the motor cortex in children.

发育中大脑运动皮质的非侵入性调制和机器人映射

Mapping the motor cortex with transcranial magnetic stimulation (TMS) has potential to interrogate motor cortex physiology and plasticity but carries ...

多功能设置研究人类电机控制用经颅磁刺激，肌电图，运动捕捉和虚拟现实

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

感觉和运动脑区与运动同步和肌电图监测功能近红外光谱在运动任务

利用经颅磁刺激，以研究人类的神经肌肉系统

合并多个数据采集系统来研究皮质输出和多段生物力学

脑状态依赖性脑刺激与实时脑脑图触发颅内磁刺激

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

用于在虚拟改良的 Box and Block 测试期间定量评估运动和肌肉活动的设置

用于在虚拟改良的 Box and Block 测试期间定量评估运动和肌肉活动的设置

用于在虚拟改良的 Box and Block 测试期间定量评估运动和肌肉活动的设置

发育中大脑运动皮质的非侵入性调制和机器人映射