Name: bouncing ball with a uniformly varying velocity in a metronome synchronization task
Uploaded: 2017-09-21T13:00:00.000+00:00
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Description: Watch this Scientific Journal Video about Bouncing Ball with a Uniformly Varying Velocity in a Metronome Synchronization Task at JoVE.com

这项工作得到了中国国家自然科学基金 (31371129) 的支持。

该协议由中山大学心理系机构审查委员会批准. 
 注意: 自定义程序和 #34; BouncingBall 和 #34; 9 是为完成此协议而提供的。提取文件和 #34; BouncingBall. zip 和 #34; 生成目录和 #34; BouncingBall 和 #34; 包含听觉和视觉刺激文件 (见下面1节); 脚本和 #34; BouncingBall_run; #34; 刺激方案的编制和响应记录 (见下文2节), 并提出刺激和录音反应 (见下文3节), 以及脚本和 #34; BouncingBall_analyze 和 #34; 用于数据分析的编程 (见下文4节) 和执行数据分析 (见下文5节).
 1. 听觉和视觉刺激的准备 注意: #34; BouncingBall 和 #34; 目录包含生成的刺激。读者可以根据需要使用或修改刺激. 
<ol> <li> 使用可以生成听觉音调的软件, 以创建600赫兹和50毫秒持续时间的纯音. </li>
	<li> 使用可以生成可视图像的软件, 创建具有透明背景的橙色球的图像. </li>
	<li> 使用带有摄像头的智能手机拍摄橙色篮球的图片, 并使用可以生成可视图像的软件, 以创建具有黑色背景的篮球图像. </li>
</ol> 2。刺激方案和响应记录的编程 注意: 在脚本和 #34 中已经实现了刺激表示和响应记录的编程; BouncingBall_run #34; 在目录和 #34 中;BouncingBall 和 #34, 可以使用文本编辑软件打开和编辑。根据脚本中的注释, 读者可以根据需要设置或修改设置. 
<ol> <li> 将背景色设置为黑色. </li>
	<li> 将每个序列设置为具有55事件 (54 IOIs)。为练习 (见下文), 将事件编号设置为 20. </li>
	<li> 将每个序列设置为重复6次。在练习中, 将重复数设置为 2. </li>
	<li> 设置学会为600毫秒或900毫秒 </li>
	<li> 按顺序构造. 
	<ol> <li> 每学会呈现纯色调. </li>
		<li> 永久显示直径为1.74 厘米的橙色球 (1.66 和 #176;) 的视觉角度和一个 3.54 cm x 4.06 厘米的白色条. 将球放在计算机屏幕的中心, 并在球的底部边缘显示条形0.92 厘米. 
		注意: 橙色球和棒被提出, 以保持尽可能一致的视觉设置之间的顺序和视觉序列, 并保持主题盯着球和保持注意的听觉任务. </li>
	</ol> </li> <li> 构造 VF 序列。
	<ol> <li> 有橙色球闪烁每学会, 即 , 它持续50毫秒, 并在余下的学会时间消失. </li>
	</ol> </li> <li> 构造 VB 序列。
	<ol> <li> 将橙色球替换为逼真的橙色篮球. </li>
		<li> 让球连续移动 0.92 cm (移动距离) 下来并且触碰白色酒吧, 然后移动到最初的位置. 
		注: 球的速度随着恒定的加速度均匀地变化。对于 2-ms 学会的 600-ms 学会或 0.09 m/s 900 , 加速度是0.20 米/秒 2 。触杆时球达到峰值速度。对不同的 IOIs 使用不同的加速度. </li>
	</ol> </li> <li> 记录并保存主题在计算机键盘上按下响应键的时间. </li> </ol>
 3. 实验过程 注意: 通过打字和 #34 来完成刺激和记录反应; BouncingBall_run (SequenceType、学会、ScreenX、ScreenY、isFormal) 和 #34; 在命令中软件的窗口。#34; ScreenX 和 #34; 和 #34; ScreenY 和 #34; 分别指 cm 中计算机屏幕的宽度和高度。攻丝数据自动记录在文件和 #34; SequenceType_IOI_ScreenX_ScreenY. 垫和 #34; 由节目。IsFormal 指的是实验是正式的实验还是实践. 
<ol> <li> 要求主题在计算机屏幕前坐60厘米的查看距离并戴上耳机. </li>
	<li> 给予主体书面知情同意书以签署. </li>
	<li> 向主题提供书面实验说明. 
	<ol> <li> 在说明中, 将节拍器同步任务解释为主题: 点击 (在键盘键上使用其首选指针的食指) 与 AT 序列中的音调同步, 在 VF 序列中闪烁的球, 以及在 VB 序列中, 弹跳球移动到最低位置 ( 即 , 触及条形图). </li>
	</ol> </li> <li> 打开该软件. 
	注: 软件连续运行, 其命令窗口保持打开状态。在命令窗口中键入 Bouncingball_run 命令将运行刺激演示文稿, 并在完成刺激演示文稿后返回到命令窗口. </li>
	<li> 要求主题与 600 ms 学会在、VF 和 VB 序列中练习两次, 以便熟悉刺激和任务. 
	注意: 实践与下面的正式实验是相同的, 除了: (1) 三序列类型的顺序不改变横跨主题;(2) 每个序列重复2次;和 (3) 每个序列有20事件。
	<ol> <li> 类型和 #34; Bouncingball_run (#39; 在和 #39;, 600, 53.1, 29.8, 0) 和 #34; 在命令窗口中, 然后按下和 #39; 输入和 #39; 键, 以按顺序执行操作. 
		注: Gan et al. 的屏幕大小为 53.1 cm x 29.8 厘米 4 , 但读者应根据所使用的屏幕分配大小。当实验程序运行时, 主体正在执行实验指令中描述的任务。此外, 序列演示程序是在进度的, 即 , 主题按空格键来启动序列. </li>
		<li> 类型和 #34; Bouncingball_run (#39; VF 和 #39;, 600, 53.1, 29.8, 0) 和 #34; 在命令窗口中, 然后按下和 #39; 输入和 #39; 按键, 以执行 vf 序列的练习. </li>
		<li> 类型和 #34; Bouncingball_run (#39; VB 和 #39;, 600, 53.1, 29.8, 0) 和 #34; 在命令窗口中, 然后按下和 #39; 输入和 #39; 按键, 以执行 vb 序列的操作. </li>
	</ol> </li> <li> 要求主题进行实验。在主题之间平衡学会类型和序列类型的顺序. 
	注意: 下面是一个主题的过程。
	<ol> <li> 类型和 #34; Bouncingball_run (#39; 在和 #39;, 600, 53.1, 29.8, 1) 和 #34; 在命令窗口中, 然后按 #39; 输入和 #39; 键, 按顺序执行 600-ms 学会。
		<ol> <li> 请注意, 主题将敲击键盘按键, 使用食指与 AT 序列中的音调同步. </li>
		</ol> </li> <li> 类型和 #34; Bouncingball_run (#39; VF 和 #39;, 600, 53.1, 29.8, 1) 和 #34; 在命令窗口中, 然后按下和 #39; 输入和 #39; 键, 以执行 600-ms 学会 VF 序列。
		<ol> <li> 请注意, 主题将使用索引手指在与闪烁球同步时敲击键盘键. </li>
		</ol> </li> <li> 类型和 #34; Bouncingball_run (#39; VB 和 #39;, 600, 53.1, 29.8, 1) 和 #34; 在命令窗口中, 然后按下和 #39; 输入和 #39; 键, 执行 600-ms 学会 vb 序列。
		<ol> <li> 请注意, 主题将在键盘键上使用食指在同步时与弹跳球移动到最低位置 ( 即 , 触及该栏) 的时刻. </li>
		</ol> </li> <li> 类型和 #34; Bouncingball_run (#39; 在和 #39;, 900, 53.1, 29.8, 1) 和 #34; 在命令窗口中, 然后按 #39; 输入和 #39; 键, 按顺序执行 900-ms 学会。
		<ol> <li> 注意, 主题将使用索引手指与 AT 序列中的音调同步敲击键盘键. </li>
		</ol> </li> <li> 类型和 #34; Bouncingball_run (#39; VF 和 #39;, 900, 53.1, 29.8, 1) 和 #34; 在命令窗口中, 然后按下和 #39; 输入和 #39; 键, 以执行 900-ms 学会 VF 序列。
		<ol> <li> 请注意, 主题将使用索引手指在与闪烁球同步时敲击键盘键. </li>
		</ol> </li> <li> 类型和 #34; Bouncingball_run (#39; VB 和 #39;, 900, 53.1, 29.8, 1) 和 #34; 在命令窗口中, 然后按下和 #39; 输入和 #39; 键, 执行 900-ms 学会 vb 序列。
		<ol> <li> 请注意, 主题将在键盘键上使用食指在同步时与弹跳球移动到最低位置 ( 即 , 触及该栏) 的时刻. </li>
		</ol> </li> </ol> </li> </ol> 4。数据分析的编程 注意: 数据分析的编程已经在脚本和 #34 中实现; BouncingBall_analyze 和 #34; 在目录和 #34; BouncingBall 和 #34;, 可以使用文本编辑打开和编辑软件.根据脚本中的注释, 读者可以根据需要设置或修改设置。原始同步数据是一个分路时间序列。使用循环方法来分析可变周期同步数据, 它已在 4 , 5 , 10 中详细说明。这里, 本协议描述了一个分析同步的稳定性 (R) 的过程, 使用循环统计工具箱 ( 例如 , CircStat 工具箱 11 ), 如甘 et al. 中所述。 4 <ol> <li> 在分路序列中省略对前五事件的分路, 因为同步通常需要几个分路器才能稳定. </li>
	<li> 计算异步. 
	<ol> <li> 对于每个分路序列, 将异步计算为分路时间与相应事件发生时间之间的差异, 从而产生 asynchronies 序列. 
		注意: 最好排除每个序列的无效分路。无效的分路包括缺少的分路器 ( 即 , 在发生事件的1/2 到 + 1/2 学会间隔期间没有分路) 和多个抽头 ( 即 , 在1/2 到 + 1/2 学会间隔期间有多个分路器). </li>
		<li> 通过异步将 asynchronies 的时间 (毫秒) 转换为角度 (度) (360/学会)。然后使用函数 circ_ang2rad 11 将度数转换为弧度, 这将导致单位圆上的相对相位 (RP). </li>
	</ol> </li> <li> 计算同步稳定性 (R). 
	<ol> <li> 对于每个异步序列, 使用函数 circ_var 11 计算退休保障的方差. </li>
		<li> 使用 r = 1-s 计算 r. 
		注: R 是该退休保障的结果的长度 ( 即 , 向量的平均值), 从 0 (不稳定攻丝与均匀分布的退休保障) 到 1 (完全稳定的攻丝与一个单极分布的退休保障). </li>
		<li> 对于每个序列类型, 计算6试验的退休保障的平均值, 作为该主题的序列类型的 R. </li>
	</ol> </li> </ol> 5。执行数据分析 注意: 下面是从上面介绍的一个主题收集的数据的分析。执行数据分析是通过打字和 #34; Bouncingball_analyze (RecordedFile) 和 #34 在软件的命令窗口中完成的, 它返回稳定性的平均值和标准偏差 (SD). 
<ol> <li> 对 600-ms 学会按顺序、类型和 #34; Bouncingball_analyze (#39; AT_600_53.1、29.8.mat 和 #39;) 和 #34; 在命令窗口中, 然后按和 #39; 输入和 #39; 密钥 </li>
	<li> 600 毫秒学会 VF 序列, 类型和 #34; Bouncingball_analyze (#39; VF_600_53.1, 29.8.mat 和 #39;) 和 #34; 在命令窗口中, 然后按 #39; 输入和 #39; 键 </li>
	<li> 600-ms 学会 VB 序列, 类型和 #34; Bouncingball_analyze (#39; VB_600_53.1, 29.8.mat 和 #39;) 和 #34; 在命令窗口中, 然后按和 #39; 输入和 #39; 键 </li>
	<li> 对于 900-ms 学会按顺序、类型和 #34; Bouncingball_analyze (#39; AT_900_53.1、29.8.mat 和 #39;) 和 #34; 在命令窗口中, 然后按 #39; 输入和 #39; 键 </li>
	<li> 900 毫秒学会 VF 序列, 类型和 #34; Bouncingball_analyze (#39; VF_900_53.1, 29.8.mat 和 #39;) 和 #34; 在命令窗口中, 然后按 #39; 输入和 #39; 键 </li>
	<li> 900-ms 学会 VB 序列, 类型和 #34; Bouncingball_analyze (#39; VB_900_53.1, 29.8.mat 和 #39;) 和 #34; 在命令窗口中, 然后按和 #39; 输入和 #39; 键 </li>
</ol>

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作者没有什么可透露的。

该协议说明了如何在节拍器同步任务中检查具有一致变化速度的弹跳球。考虑到它的同步性能与听觉音调, 弹跳球是特别重要的, 以解决当前的研究课题的 SMS 是否是特定模式。
当前协议中的关键步骤是引入弹跳球的均匀变化速度, 并提供 step-by 步指令来执行同步任务并分析同步数据。本协议还说明了如何使用不同的加速度在不同的 IOIs 弹跳球。在这里应该提到的是, 弹跳球的使用应限制在 IOIs 不少于 300 ms 甘et al.4显示弹跳球与 300 ms 学会是太快, 看起来不自然的主题, 因此很难利用球。
弹跳球是研究 SMS 和定时处理的有用工具。在这个协议中, 弹跳球是在一个简单的节拍器同步任务中说明的, 而代表性的结果是从一个正常的受试者的行为研究, 未来的工作可以采取弹跳球的调查: (1) 同步更复杂的节奏序列, 节拍器 (或节拍, 在音乐的上下文) 需要从复杂的序列中提取12,13;(2) 节拍器中的定时偏差的知觉13,14;(3) SMS6的基本神经机制;和 (4) 定时缺损患者,例如, 帕金森患者15,16。

运动同步 (SMS) 指的是动作 (例如、手指敲击) 与外部节奏的协调, 并使用一个简单的节拍器同步任务来进行规范研究, 在这种情况下, 需要用手指敲击一个同步序列1,2。一个多世纪以来, 节拍器同步中听觉视觉模式的优越性已经建立起来: 对由听觉音调 (图 1A) 组成的听觉序列, 同步比对视觉序列更稳定由视觉闪烁 (图 1B)1组成。然而, 节拍器同步的这种听觉优势最近受到了使用周期性移动视觉刺激的研究的挑战3,4,5,6 (注意周期性地移动视觉刺激提到连续的运动)。霍夫et al.使用一个由上下条移动的可视序列组成的恒定速度, 并发现上下条的同步比视觉闪烁的同步更稳定, 但仍然不如同步的稳定听觉音调3,6。伊韦尔森et al.使用了一个弹跳球, 它的速度根据整流正弦波的不同而变化, 并显示弹跳球的同步接近听觉音调的同步5。最近, Gan et al.使用了一个具有一致变化速度 (即, 模拟重力影响) 的弹跳球 (图 1C), 并发现弹跳球的同步性不低于同步听觉音调4。
当前协议的目的是引入一个程序, 在节拍器同步任务中应用一个具有一致变速的弹跳球, 如 Gan et al.中所述。4节拍器同步任务包括由听觉音调组成的听觉序列 (按顺序排列,图 1A), 以及由视觉闪烁组成的视觉序列 (VF 序列,图 1B), 在 SMS 中被广泛采用研究1。任务中的第三种序列是由弹跳球组成的可视序列 (VB 序列,图 1C)。而特定模式的机制长期以来一直被认为是短信的铺垫, 如听觉和运动神经皮层之间的连接比视觉和运动神经皮层2之间的联系更紧密, sms 是否是特定于最近的模式研究注意1,7。本协议中介绍的弹跳球对于解决模态问题特别有用, 因为弹跳球和听觉音调的同步性能是可比的。此外, 节拍器同步可以在有限的学会 (100-1、800毫秒)8范围内进行灵活的执行。为了说明弹跳球对不同 IOIs 的应用, 目前的协议包括一个600毫秒的学会 (这大约是最喜欢的学会), 和一个900毫秒的学会。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56205/56205fig1.jpg"> 
图 1:刺激的例证。这个主题按一个同步序列来敲击, 它由听觉音调 (A: AT 序列)、视觉闪烁球 (B: VF 序列) 或视觉弹跳球 (C: VB 序列) 组成。在C中, 弹跳球的速度和轨迹被绘制为时间函数, 分别用蓝线和绿线条表示。弹跳球的运动距离为 9.2 mm, 在弹跳点的峰值速度 (即, 在最低的球位) 是0.061 毫米/ms 八事件在 600-ms 学会序列显示。<a href="//ecsource.jove.com/files/ftp_upload/56205/56205fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

<table><tbody><tr><td>Psychtoolbox</td><td>http://psychtoolbox.org</td><td>3.0.12</td><td></td></tr><tr><td>MATLAB</td><td>MathWorks</td><td>7.11.0 (R2010b)</td><td></td></tr><tr><td>Adobe Photoshop</td><td>Adobe&amp;nbsp;Systems</td><td>Adobe Photoshop CS6</td><td></td></tr><tr><td>computer monitor</td><td>AOC</td><td>G2460PQU/BR LCD</td><td></td></tr><tr><td>headphone</td><td>PHILIPS</td><td>SHM6500</td><td></td></tr><tr><td>computer keyboard</td><td>Dell</td><td>kb113t</td><td></td></tr><tr><td>smart phone</td><td>Apple</td><td>iphone6s</td><td></td></tr><tr><td>IBM SPSS Statistics</td><td>IBM</td><td>IBM SPSS Statistics 21</td><td></td></tr></tbody></table>

bouncing ball with a uniformly varying velocity in a metronome synchronization task

运动同步 (SMS), 一个基本的人的能力协调运动与外在节奏, 长期被认为是形式具体的。在标准节拍器同步任务中, 需要用一个手指和一个等时序列来敲击, 一个公认的发现是, 同步对由听觉音调组成的听觉序列要比对视觉由视觉闪光组成的序列。然而, 最近的研究表明, 周期性地移动视觉刺激可以大大改善同步与视觉闪光。特别是, 同步的视觉弹跳球, 具有一致的变化速度被发现是不低于稳定比同步的听觉音调。在这里, 当前的协议描述了在节拍器同步任务中具有一致变速的弹跳球的应用。在不同 inter-onset 间隔 (学会) 的序列中使用弹跳球。该代表的结果说明了弹跳球的同步性能, 与听觉音调和视觉闪光的表现相比较。考虑到它与听觉音调的同步性能, 弹跳球对于解决当前的研究课题, 特别是情态机制是否是 SMS, 具有特别重要的意义。

在 SMS 研究中最著名的结果之一是, 节拍器同步对由听觉音调组成的听觉序列比对由视觉闪烁1组成的视觉序列更稳定, 这意味着特定于模式的机制SMS2。然而, 最近的研究表明, 与视觉闪光相比, 周期性地移动视觉刺激可以大大改善同步3,4,5,6, 以及同步视觉弹跳球有一个一致的变化速度被发现是不低于稳定比同步的听觉音调4。代表性结果是我们组4的已发布工作的示例。实验中有15科目。two-way 重复测量方差分析 (变异方差, 与温室 Geisser 校正) 与因素序列类型 (三序列类型) 和学会类型 (二学会类型) 显露了序列类型的统计主要作用 (F228 =16.77, p = 0.001, partialη2 = 0.55)。学会类型的主要效果 (F114 = 0.88, p = 0.364,部分η2 = 0.06) 和两个因素之间的交互 (F228 = 0.88, p = 0.401,部分η2= 0.06) 没有统计学意义。对序列类型 (t 检验, 与 Bonferroni 校正) 的稳定性的比较表明, 对于 600 ms 和 900-ms IOIs, 弹跳球的同步比同步的视觉闪光更稳定 (600 毫秒学会: t14 = 3.96, pcorreccted = 0.006,科恩的 d = 1.02;900-ms 学会: t14 = 4.28, pcorreccted = 0.006,科恩的 d = 1.11), 并且不低于听觉音调的同步 (600-ms 学会: t14 = 2.95, pcorreccted = 0.066,科恩的 d = 0.76;900-ms 学会: t14 = 2.06, pcorreccted = 0.348,科恩的 d = 0.53) (图 2)。
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56205/56205fig2.jpg"> 
图 2: 用于 AT、VF 和 VB 序列的 600-毫秒和 900-ms IOIs 的同步稳定性 (R).误差线指示±95% 置信区间。其他约定如图 1所示。该图从 Gan et al.中的图 2改编4 (这是在一个创造性的共用归属4.0 国际许可下发布的)。<a href="//ecsource.jove.com/files/ftp_upload/56205/56205fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Bouncing Ball with a Uniformly Varying Velocity in a Metronome Synchronization Task at JoVE.com

Bouncing Ball with a Uniformly Varying Velocity in a Metronome Synchronization Task

节拍器同步任务中具有均匀变速的弹跳球

本协议的目的是在节拍器同步任务中引入一个具有一致变速的弹跳球的应用。

Sensorimotor synchronization (SMS), a fundamental human ability to coordinate movements with external rhythms, has long been thought to be modality ...

bouncing-ball-with-uniformly-varying-velocity-metronome

Nanyang Technological University

Research

JoVE Journal

Behavior

5.9K 次观看.  Sun Yat-Sen University. 本协议的目的是在节拍器同步任务中引入一个具有一致变速的弹跳球的应用。

视频: Bouncing Ball with a Uniformly Varying Velocity in a Metronome Synchronization Task

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here with the goal of uncovering rhythm disorders, such as beat deafness. Beat deafness is characterized by poor performance in perceiving durations in auditory rhythmic patterns or poor synchronization of movement with auditory rhythms (e.g., with musical beats). These tasks include the synchronization of finger tapping to the beat of simple and complex auditory stimuli and the detection of rhythmic irregularities (anisochrony detection task) embedded in the same stimuli. These tests, which are easy to administer, include an assessment of both perceptual and sensorimotor timing abilities under different conditions (e.g., beat rates and types of auditory material) and are based on the same auditory stimuli, ranging from a simple metronome to a complex musical excerpt. The analysis of synchronized tapping data is performed with circular statistics, which provide reliable measures of synchronization accuracy (e.g., the difference between the timing of the taps and the timing of the pacing stimuli) and consistency. Circular statistics on tapping data are particularly well-suited for detecting individual differences in the general population. Synchronized tapping and anisochrony detection are sensitive measures for identifying profiles of rhythm disorders and have been used with success to uncover cases of poor synchronization with spared perceptual timing. This systematic assessment of perceptual and sensorimotor timing can be extended to populations of patients with brain damage, neurodegenerative diseases (e.g., Parkinson&#8217;s disease), and developmental disorders (e.g., Attention Deficit Hyperactivity Disorder).

Behavioral tasks that allow for the assessment of perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) are presented. Synchronization of finger tapping to the beat of an auditory stimuli and detecting rhythmic irregularities provides a means of uncovering rhythm disorders.

揭开节拍耳聋:检测节律紊乱与同步手指敲击和感知定时任务

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here ...

科研

行为学

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

For slender and lightweight structures, vibration serviceability is a matter of growing concern, often constituting the critical design requirement. With designs governed by the dynamic performance under human-induced loads, a strong demand exists for the verification and refinement of currently available load models. The present contribution uses a 3D inertial motion tracking technique for the characterization of the in-field pedestrian behavior. The technique is first tested in laboratory experiments with simultaneous registration of the corresponding ground reaction forces. The experiments include walking persons as well as rhythmical human activities such as jumping and bobbing. It is shown that the registered motion allows for the identification of the time variant pacing rate of the activity. Together with the weight of the person and the application of generalized force models available in literature, the identified time-variant pacing rate allows to characterize the human-induced loads. In addition, time synchronization among the wireless motion trackers allows identifying the synchronization rate among the participants. Subsequently, the technique is used on a real footbridge where both the motion of the persons and the induced structural vibrations are registered. It is shown how the characterized in-field pedestrian behavior can be applied to simulate the induced structural response. It is demonstrated that the in situ identified pacing rate and synchronization rate constitute an essential input for the simulation and verification of the human-induced loads. The main potential applications of the proposed methodology are the estimation of human-structure interaction phenomena and the development of suitable models for the correlation among pedestrians in real traffic conditions.

A protocol is presented for the characterization of the in-field pedestrian behavior and the simulation of the resulting structural response. Field-tests demonstrate that the in situ identified pacing rate and synchronization rate among the participants constitute an essential input for the simulation and verification of the human-induced loads.

基于该特征场行人行为人类引起的振动模拟

For slender and lightweight structures, vibration serviceability is a matter of growing concern, often constituting the critical design requirement. With ...

工程学

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Path integration is a process in which self-motion is integrated over time to obtain an estimate of one's current position relative to a starting point 1. Humans can do path integration based exclusively on visual 2-3, auditory 4, or inertial cues 5. However, with multiple cues present, inertial cues - particularly kinaesthetic - seem to dominate 6-7. In the absence of vision, humans tend to overestimate short distances (&lt;5 m) and turning angles (&lt;30&deg;), but underestimate longer ones 5. Movement through physical space therefore does not seem to be accurately represented by the brain.
Extensive work has been done on evaluating path integration in the horizontal plane, but little is known about vertical movement (see 3 for virtual movement from vision alone). One reason for this is that traditional motion simulators have a small range of motion restricted mainly to the horizontal plane. Here we take advantage of a motion simulator 8-9 with a large range of motion to assess whether path integration is similar between horizontal and vertical planes. The relative contributions of inertial and visual cues for path navigation were also assessed.
16 observers sat upright in a seat mounted to the flange of a modified KUKA anthropomorphic robot arm. Sensory information was manipulated by providing visual (optic flow, limited lifetime star field), vestibular-kinaesthetic (passive self motion with eyes closed), or visual and vestibular-kinaesthetic motion cues. Movement trajectories in the horizontal, sagittal and frontal planes consisted of two segment lengths (1st: 0.4 m, 2nd: 1 m; &plusmn;0.24 m/s2 peak acceleration). The angle of the two segments was either 45&deg; or 90&deg;. Observers pointed back to their origin by moving an arrow that was superimposed on an avatar presented on the screen.
Observers were more likely to underestimate angle size for movement in the horizontal plane compared to the vertical planes. In the frontal plane observers were more likely to overestimate angle size while there was no such bias in the sagittal plane. Finally, observers responded slower when answering based on vestibular-kinaesthetic information alone. Human path integration based on vestibular-kinaesthetic information alone thus takes longer than when visual information is present. That pointing is consistent with underestimating and overestimating the angle one has moved through in the horizontal and vertical planes respectively, suggests that the neural representation of self-motion through space is non-symmetrical which may relate to the fact that humans experience movement mostly within the horizontal plane.

An efficient way to gain insight into how humans navigate themselves in three dimensions is described. The method takes advantage of a motion simulator capable of moving observers in ways unattainable by traditional simulators. Results confirm that movement in the horizontal plane is underestimated, while vertical movement is overestimated.

MPI Cyber​​Motion模拟器：一种新型的运动模拟器的执行情况调查三个维度的多感官的路径积分

Path integration is a process in which self-motion is integrated over time to obtain an estimate of one's current position relative to a starting point 1. ...

神经科学

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

The fields that develop methods for sensory substitution and sensory augmentation have aimed to control external goals using signals from the central nervous systems (CNS). Less frequent however, are protocols that update external signals self-generated by interactive bodies in motion. There is a paucity of methods that combine the body-heart-brain biorhythms of one moving agent to steer those of another moving agent during dyadic exchange. Part of the challenge to accomplish such a feat has been the complexity of the setup using multimodal bio-signals with different physical units, disparate time scales and variable sampling frequencies.
In recent years, the advent of wearable bio-sensors that can non-invasively harness multiple signals in tandem, has opened the possibility to re-parameterize and update the peripheral signals of interacting dyads, in addition to improving brain- and/or body-machine interfaces. Here we present a co-adaptive interface that updates efferent somatic-motor output (including kinematics and heart rate) using biosensors; parameterizes the stochastic bio-signals, sonifies this output, and feeds it back in re-parameterized form as visuo/audio-kinesthetic reafferent input. We illustrate the methods using two types of interactions, one involving two humans and another involving a human and its avatar interacting in near real time. We discuss the new methods in the context of possible new ways to measure the influences of external input on internal somatic-sensory-motor control.

We present protocols and methods of analyses to build co-adaptive interfaces that stream, parameterize, analyze, and modify human body and heart signals in close-loop. This setup interfaces signals derived from the peripheral and central nervous systems of the person with external sensory inputs to help track biophysical change.

使用闭环接口实时代理控制重新参数化的外围信号

The fields that develop methods for sensory substitution and sensory augmentation have aimed to control external goals using signals from the central ...

研究视觉持续时间感知任务中的动眼神经反应

Eye Movements in Visual Duration Perception: Disentangling Stimulus from Time in Predecisional Processes

Eye-tracking methods may allow the online monitoring of cognitive processing during visual duration perception tasks, where participants are asked to estimate, discriminate, or compare time intervals defined by visual events like flashing circles. However, and to our knowledge, attempts to validate this possibility have remained inconclusive so far, and results remain focused on offline behavioral decisions made after stimulus appearance. This paper presents an eye-tracking protocol for exploring the cognitive processes preceding behavioral responses in an interval comparison task, where participants viewed two consecutive intervals and had to decide whether it speeded up (first interval longer than second) or slowed down (second interval longer). 
Our main concern was disentangling oculomotor responses to the visual stimulus itself from correlates of duration related to judgments. To achieve this, we defined three consecutive time windows based on critical events: baseline onset, the onset of the first interval, the onset of the second interval, and the end of the stimulus. We then extracted traditional oculomotor measures for each (number of fixations, pupil size) and focused on time-window-related changes to separate the responses to the visual stimulus from those related to interval comparison per se. As we show in the illustrative results, eye-tracking data showed significant differences that were consistent with behavioral results, raising hypotheses on the mechanisms engaged. This protocol is embryonic and will require many improvements, but it represents an important step forward in the current state of art.

作者聚焦：探索视觉刺激的时间感知与阅读技能之间的联系

We present a protocol that employs eye tracking to monitor eye movements during an interval comparison (duration perception) task based on visual events. The aim is to provide a preliminary guide to separate oculomotor responses to duration perception tasks (comparison or discrimination of time intervals) from responses to the stimulus itself.

视觉持续时间感知中的眼球运动：在决策前过程中将刺激与时间解开

Eye-tracking methods may allow the online monitoring of cognitive processing during visual duration perception tasks, where participants are asked to ...

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.

节拍器同步任务中具有均匀变速的弹跳球

摘要

探索更多视频

此视频中的章节

揭开节拍耳聋:检测节律紊乱与同步手指敲击和感知定时任务

基于该特征场行人行为人类引起的振动模拟

MPI CyberMotion模拟器：一种新型的运动模拟器的执行情况调查三个维度的多感官的路径积分

使用闭环接口实时代理控制重新参数化的外围信号

视觉持续时间感知中的眼球运动：在决策前过程中将刺激与时间解开

视觉持续时间感知中的眼球运动：在决策前过程中将刺激与时间解开

视觉持续时间感知中的眼球运动：在决策前过程中将刺激与时间解开

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

节拍器同步任务中具有均匀变速的弹跳球

摘要

探索更多视频

此视频中的章节

揭开节拍耳聋:检测节律紊乱与同步手指敲击和感知定时任务

基于该特征场行人行为人类引起的振动模拟

MPI Cyber​​Motion模拟器：一种新型的运动模拟器的执行情况调查三个维度的多感官的路径积分

使用闭环接口实时代理控制重新参数化的外围信号

视觉持续时间感知中的眼球运动：在决策前过程中将刺激与时间解开

视觉持续时间感知中的眼球运动：在决策前过程中将刺激与时间解开

视觉持续时间感知中的眼球运动：在决策前过程中将刺激与时间解开

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

MPI CyberMotion模拟器：一种新型的运动模拟器的执行情况调查三个维度的多感官的路径积分