该研究得到了清华大学倡议科学研究计划（智能设备上曲面键盘的人体工程学设计）的支持。作者感谢刘天宇对图形的善意建议和编码帮助。

该研究是按照伦理原则进行的，并得到了清华大学伦理委员会的批准。 图1 显示了评估智能手机键盘设计的过程。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61796/61796fig01.jpg"> 图 1：进行键盘实验和评估键盘设计的一般过程。<a href="https://www.jove.com/files/ftp_upload/61796/61796fig01large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
1. 准备工作
<ol><li>
实验设计
	<ol>
<li>定义研究问题并提出假设。</li>
		<li>根据假设设计实验并定义自变量（例如，键盘布局，打字姿势）。使用受试者内部设计，以减少参与者之间差异引起的混杂因素和方差。</li>
	</ol>
</li>
	<li>
因变量
	<ol>
<li>使用物理数据，包括手的长度，输入手指的长度和输入手指的周长，这些都是用卷尺测量的，如图 2所示。</li>
		<li>使用生理数据，包括皮肤电反应（由便携式无线生理检测仪测量）、心率（由便携式无线生理检测仪测量）、肌电活动（通过表面肌电图测量）等。</li>
		<li>使用输入性能：每分钟字数、字错误率和两个键之间的转换时间。<ol>
<li>每分钟字数是指参与者的输入速度（即每分钟正确输入的字数）。</li>
			<li>单词错误率是指参与者的输入准确性（即，输入错误的单词数除以一个条件下的总单词数）。纠正的错误率，未纠正的错误率和总错误率也在以前的研究中使用过36。</li>
			<li>两个键之间的转换时间是指参与者在正确输入的单词22 的两个接触点之间的反应时间（即，第二个接触点的开始时间减去第一个字符的离开时间）。</li>
		</ol>
</li>
		<li>使用身体运动数据，如手势和身体（手指）运动。它们可以通过动作捕捉系统35收集。</li>
		<li>使用主观数据，例如感知的可用性，使用意图，感知的准确性和速度，感知的劳累和疼痛以及主观工作量等。主观数据可以通过现有的量表和问卷获得，这些量表和问卷高度可靠，可以更好地评估参与者对键盘设计的主观反馈。<ol>
<li>使用 NASA-TLX，这是一个 21 分量表，用于通过心理、身体、时间、绩效、努力和挫折维度来衡量主观工作量。高分表示主观工作量高26。</li>
			<li>使用系统可用性量表，这是一个包含10个项目的5分问卷，一个参与者的回答将计算为从0到100的单个分数。高分表示感知可用性高24。</li>
			<li>使用Borg CR10量表，范围从0到10来测量感知到的疼痛和劳累。高分表示感觉到疼痛和劳累水平高25。</li>
			<li>使用意向使用量表：一个 10 点调查问卷，用于衡量参与者使用技术或产品的可能性。高分表示高水平可能性28。</li>
			<li>感知速度和感知精度都是通过50分制来衡量的，高分表示良好的感知性能28。</li>
		</ol>
</li>
		<li>收集每个接触点的坐标数据，并将其更改为每个按钮30，31上接触点的拟合椭圆（95%CI）。采用每个拟合椭圆的面积以及从拟合椭圆的中心到每个按钮的目标中心的偏移量作为因变量。 注：坐标数据可通过智能手机上自主开发的应用程序精确采集。如果很难获得坐标数据，客观和主观数据就足以粗略地评估键盘设计。</li>
	</ol>
</li>
</ol><img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61796/61796fig2v4.jpg"> 图2：手的测量值。<a href="https://www.jove.com/files/ftp_upload/61796/61796fig2v4large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<ol start="3"><li>
材料
	<ol>
<li>选择实验智能手机。考虑重量、分辨率和屏幕尺寸。</li>
		<li>在智能手机上设计和开发实验软件（可选步骤）。 注：两个按键之间的转换时间可通过此软件或运动捕捉传感器（即加速度计传感器）自动记录。手动收集它可能很困难（例如，时钟或秒表）。</li>
		<li>根据假设从以下建议中选择输入任务，并对其进行修改以匹配研究目的。<ol>
<li>对于字符对输入任务，将 26 个英文字母随机配对为 676 对，并根据实验设计将它们平均分成几组。</li>
			<li>对于短语（句子）输入任务，请使用长度适中、易于记忆且代表目标语言的短语。如果目标语言是英语，请从500个短语集37中提取15-20个（或基于研究目的）短语或单词。</li>
		</ol>
</li>
	</ol>
</li>
	<li>
参与者招募
	<ol>
<li>使用 G*Power 软件计算样本数量。</li>
		<li>发布调查问卷以招募潜在参与者。</li>
		<li>过滤具有所需特征的潜在参与者，例如年龄，健康，视力，利手性和输入经验。确保参与者的输入体验是平衡的。</li>
	</ol>
</li>
</ol>2. 程序
<ol><li>向参与者宣读实验的知情同意书，包括实验程序，任务以及他们是否会遇到任何精神或身体伤害。如果参与者同意参加，他们需要签署知情同意书。如果没有，他们可以立即退出。根据知情同意书，参与者也可以在实验的任何阶段退出。</li>
	<li>收集物理和人口统计数据。使用卷尺测量每个参与者的手（图2），以消除手的大小差异的影响，并为未来的研究提供可重复的数据。收集人口统计数据，如年龄、性别、精确的输入经验和职业。</li>
	<li>对所有设备进行消毒，并清洁将接触设备的参与者的身体部位。<ol>
<li>要求参与者洗手并清洁智能手机的屏幕，以便智能手机的传感器更加敏感。</li>
		<li>要求参与者佩戴便携式无线生理探测器或动作捕捉系统。要求参与者在非惯用手上佩戴便携式无线生理检测腕带，以记录皮肤电反应和心率，避免噪音干扰。<ol>
<li>将动作捕捉系统的被动标记放在指甲、手指近端指骨、颈椎（C3-C5）和手臂上，以收集精确的身体和手指运动。将无线电极贴在两只手臂和两只前臂的皮肤上，以检测肌电图活动（可选步骤）。</li>
		</ol>
</li>
		<li>校准实验中使用的所有设备。</li>
	</ol></li>
	<li>练习部分<ol>
<li>让参与者完成训练任务。训练任务用于提高参与者对输入任务和键盘的熟悉程度，以减少练习或不熟悉对实验结果的影响。它由从676个英语对集或500个短语集中随机选择的50对或20个单词组成。只有当他们的输入准确率在150秒内达到80%或更高时，他们才能进入正式试验。示例研究采用输入50对作为训练任务。</li>
	</ol></li>
	<li>主要任务<ol>
<li>让参与者在所有实验条件下完成正式试验。在输入任务期间，它们需要尽快确保其准确性。正式试验是真正的投入任务，将在研究中进行评估和分析。每个对、单词或句子代表一个试验，不同的实验设计产生不同的实验条件。</li>
		<li>让参与者按随机顺序或平衡顺序完成输入任务。输入材料的划分方法如下。首先，676对可以随机分为每个实验条件（即，参与者在完成所有实验条件时都进入了所有对）。其次，在每个实验条件下，676对可以随机分成几个块，参与者需要随机完成这些块。第三，为了输入单词，参与者需要在每个条件下完成大约20项试验。第四，对于输入句子，参与者需要在每个条件下完成大约10-15次试验。研究人员应确保在每个条件下，参与者输入的字符数和单词数之间没有显着差异。示例性研究采用第一种方法，并具有四个实验条件。</li>
		<li>在每个条件之后，要求参与者随机完成所有问卷（评估其主观体验的量表），并给他们1分钟或更长时间的休息时间。</li>
	</ol></li>
	<li>在实验结束时，让每个参与者完成综合问卷（Q&A），以获得主观反馈。</li>
	<li>向参与者表示感谢，并提供金钱或物质奖励。</li>
</ol>3. 数据分析
<ol><li>
通过适当的参数化或非参数化检验进行假设检验
	<ol>
<li>分析身体，生理和身体运动数据，以测试参与者之间的差异是否会显着影响用户的结果和不表达的输入体验（可选步骤）。</li>
		<li>分析参与者的输入性能，以测试键盘上的输入效率。</li>
		<li>分析主观数据以测试键盘的感知可用性和主观反馈。</li>
		<li>弄清楚练习效果和疲劳效果是否对结果有显著影响。对于每个条件，试验根据时间戳分为两部分（即前半部分和后半部分）。具体来说，在每个条件下，检查前半部分和后半部分之间的输入性能差异，以测试是否存在练习效应或疲劳效应。</li>
		<li>分析每个按钮上接触点的拟合椭圆的面积以及从其中心到每个按钮的目标中心的偏移量（可选步骤）。<ol>
<li>使用软件收集每个按钮的所有接触点，它们大致符合二元高斯分布。每个按钮在 x 和 y 方向上的 95% 置信区间是通过每个接触点的坐标数据（以像素为单位）得出的，每个键盘按钮的 1：1 轮廓上的 95% 置信度椭圆是通过像素坐标上的 Python 脚本拟合的（请参见编码文件 2）。</li>
			<li>使用拟合椭圆 （95% CI） 及其面积来演示每个按钮上接触点的分散性。在每个按钮中，由 Python 脚本计算的拟合椭圆的偏移量定义为拟合椭圆到按钮目标点的中心点，并且可以从 x 和 y 方向表示（即，在 X 轴和 Y 轴中，请参见编码文件 3）。</li>
		</ol>
</li>
	</ol>
</li>
	<li>
建模和仿真
	<ol>
<li>使用数据驱动模型作为键盘位置和方向的函数来预测 Python 脚本的手指移动。手指的所有运动分为八个方向38（ 从上到下，从底部到顶部，从左到右，从右到左，从左到上到右-下，从右到下到左-上，从左到下到右-上，右-上到左-底）。对于每个方向，计算两个键之间的平均过渡时间以表示手指移动的有效性，用于评估键盘设计（可选步骤）。</li>
		<li>使用线性回归分析构建增强的 Fitts 定律（或其扩展版本 FFitts 定律）模型，以使用 Python 脚本的集成认知架构39 预测两个关键键之间的转换时间。增强的Fitts定律模型可以基于其对按键位置和有效宽度以及两个键的距离（可选步骤）的分析，对键盘设计提供更好的预测和评估。</li>
	</ol>
</li>
</ol>

<ol>
	<li>Lee, S., Zhai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+performance+of+touch+screen+soft+buttons.">The performance of touch screen soft buttons.</a> Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2009).</li><li>Smith, B. A., Bi, X., Zhai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimizing+touchscreen+keyboards+for+gesture+typing.">Optimizing touchscreen keyboards for gesture typing.</a> Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. , (2015).</li><li>. Global smartphone penetration rate as share of population from 2016 to 2020 [Fact sheet] Available from: <a target="_blank" href="https://www.statista.com/statistics/203734/global-smartphone-penetration-per-capita-since-2005">https://www.statista.com/statistics/203734/global-smartphone-penetration-per-capita-since-2005</a> (2020)</li><li>Top Countries by Smartphone Users [Fact sheet]. Newzoo Available from: <a target="_blank" href="https://newzoo.com/insights/rankings/top-countries-by-smartphone-penetration-and-users">https://newzoo.com/insights/rankings/top-countries-by-smartphone-penetration-and-users</a> (2019)</li><li>Gboard - the Google Keyboard [Press release]. Google Play Available from: <a target="_blank" href="https://play.google.com/store/apps/details?id=com.google.android.inputmethod.latin">https://play.google.com/store/apps/details?id=com.google.android.inputmethod.latin</a> (2020)</li><li>Eitivipart, A. C., Viriyarojanakul, S., Redhead, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Musculoskeletal+disorder+and+pain+associated+with+smartphone+use:+A+systematic+review+of+biomechanical+evidence.">Musculoskeletal disorder and pain associated with smartphone use: A systematic review of biomechanical evidence.</a> Hong Kong Physiotherapy Journal. 38 (2), 77-90 (2018).</li><li>Chang, J., Choi, B., Tjolleng, A., Jung, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+button+position+on+a+soft+keyboard:+Muscle+activity,+touch+time,+and+discomfort+in+two-thumb+text+entry.">Effects of button position on a soft keyboard: Muscle activity, touch time, and discomfort in two-thumb text entry.</a> Applied Ergonomics. 60, 282-292 (2017).</li><li>Gehrmann, S. V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Motion+deficit+of+the+thumb+in+CMC+joint+arthritis.">Motion deficit of the thumb in CMC joint arthritis.</a> Journal of Hand Surgery. 35 (9), 1449-1453 (2010).</li><li>Kim, G., Ahn, C. S., Jeon, H. W., Lee, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+the+Use+of+Smartphones+on+Pain+and+Muscle+Fatigue+in+the+Upper+Extremity.">Effects of the Use of Smartphones on Pain and Muscle Fatigue in the Upper Extremity.</a> Journal of Physical Therapy Science. 24 (12), 1255-1258 (2012).</li><li>Girouard, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=One-handed+bend+interactions+with+deformable+smartphones.">One-handed bend interactions with deformable smartphones.</a> Proceedings of the 33rd annual ACM conference on human factors in computing systems. , (2015).</li><li>Lee, M., Hong, Y., Lee, S., Won, J., Yang, J., Park, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+smartphone+use+on+upper+extremity+muscle+activity+and+pain+threshold.">The effects of smartphone use on upper extremity muscle activity and pain threshold.</a> Journal of Physical Therapy Science. 27 (6), 1743-1745 (2015).</li><li>Word Flow keyboard [Press release]. Microsoft Garage Available from: <a target="_blank" href="https://www.microsoft.com/en-us/garage/profiles/word-flow-keyboard/">https://www.microsoft.com/en-us/garage/profiles/word-flow-keyboard/</a> (2020)</li><li>The glory of kings [Press release]. Tencent Games Available from: <a target="_blank" href="https://pvp.qq.com/">https://pvp.qq.com/</a> (2020)</li><li>Bi, X., Zhai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ijqwerty:+what+difference+does+one+key+change+make?+Gesture+typing+keyboard+optimization+bounded+by+one+key+position+change+from+qwerty.">Ijqwerty: what difference does one key change make? Gesture typing keyboard optimization bounded by one key position change from qwerty.</a> Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. , (2016).</li><li>Bi, X., Smith, B. A., Zhai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quasi-qwerty+soft+keyboard+optimization.">Quasi-qwerty soft keyboard optimization.</a> Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2010).</li><li>Fitts, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+information+capacity+of+the+human+motor+system+is+controlled+by+the+amplitude+of+movement.">The information capacity of the human motor system is controlled by the amplitude of movement.</a> Journal of Experimental Psychology. 47, 381-391 (1954).</li><li>Bi, X., Li, Y., Zhai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FFitts+law:+modeling+finger+touch+with+fitts'+law.">FFitts law: modeling finger touch with fitts' law.</a> Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2013).</li><li>Dunlop, M., Levine, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multidimensional+pareto+optimization+of+touchscreen+keyboards+for+speed,+familiarity+and+improved+spell+checking.">Multidimensional pareto optimization of touchscreen keyboards for speed, familiarity and improved spell checking.</a> Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2012).</li><li>Li, Y., Chen, L., Goonetilleke, 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=A+heuristic-based+approach+to+optimize+keyboard+design+for+single-finger+keying+applications.">A heuristic-based approach to optimize keyboard design for single-finger keying applications.</a> International Journal of Industrial Ergonomics. 36 (8), 695-704 (2006).</li><li>Benligiray, B., Topal, C., Akinlar, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SliceType:+fast+gaze+typing+with+a+merging+keyboard.">SliceType: fast gaze typing with a merging keyboard.</a> Journal on Multimodal User Interfaces. 13 (4), 321-334 (2019).</li><li>Wang, Y., Ai, H., Liang, Q., Chang, W., He, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+to+optimize+the+input+efficiency+of+keyboard+buttons+in+large+smartphone?+A+comparison+of+curved+keyboard+and+keyboard+area+size+[Conference+presentation].">How to optimize the input efficiency of keyboard buttons in large smartphone? A comparison of curved keyboard and keyboard area size [Conference presentation].</a> International Conference on Human-Computer Interaction. , (2019).</li><li>Bergstrom-Lehtovirta, J., Oulasvirta, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+the+functional+area+of+the+thumb+on+mobile+touchscreen+surfaces.">Modeling the functional area of the thumb on mobile touchscreen surfaces.</a> Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2014).</li><li>Brooke, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SUS:+A+retrospective.">SUS: A retrospective.</a> Journal of Usability Studies. 8 (2), 29-40 (2013).</li><li>Borg, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Principles+in+scaling+pain+and+the+Borg+CR+Scales.">Principles in scaling pain and the Borg CR Scales.</a> Psychologica. 37, 35-47 (2004).</li><li>Hart, S. G., Staveland, L. E., Hancock, P. A., Meshkati, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+NASA-TLX+(task+load+index):+results+of+empirical+and+theoretical+research.">Development of NASA-TLX (task load index): results of empirical and theoretical research.</a> Human mental workload. , 139-183 (1988).</li><li>Trudeau, M. B., Asakawa, D. S., Jindrich, D. L., Dennerlein, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Two-handed+grip+on+a+mobile+phone+affords+greater+thumb+motor+performance,+decreased+variability,+and+a+more+extended+thumb+posture+than+a+one-handed+grip.">Two-handed grip on a mobile phone affords greater thumb motor performance, decreased variability, and a more extended thumb posture than a one-handed grip.</a> Applied Ergonomics. 52, 24-28 (2016).</li><li>Turner, C. J., Chaparro, B. S., He, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Text+input+on+a+smartwatch+qwerty+keyboard:+tap+vs.+trace.">Text input on a smartwatch qwerty keyboard: tap vs. trace.</a> International Journal of Human Computer Interaction. 33 (1-3), 143-150 (2017).</li><li>Zhai, S., Kristensson, P. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+word-gesture+keyboard:+reimagining+keyboard+interaction.">The word-gesture keyboard: reimagining keyboard interaction.</a> Communications of the ACM. 55 (9), 91-101 (2012).</li><li>Azenkot, S., Zhai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Touch+behavior+with+different+postures+on+soft+smartphone+keyboards.">Touch behavior with different postures on soft smartphone keyboards.</a> Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services. , (2012).</li><li>Yi, X., Yu, C., Shi, W., Shi, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Is+it+too+small?:+Investigating+the+performances+and+preferences+of+users+when+typing+on+tiny+qwerty+keyboards.">Is it too small?: Investigating the performances and preferences of users when typing on tiny qwerty keyboards.</a> International Journal of Human Computer Studies. 106, 44-62 (2017).</li><li>Li, Y., You, F., Ji, M., You, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Smartphone+text+input:+effects+of+experience+and+phrase+complexity+on+user+performance,+physiological+reaction,+and+perceived+usability.">Smartphone text input: effects of experience and phrase complexity on user performance, physiological reaction, and perceived usability.</a> Applied Ergonomics. 80, 200-208 (2019).</li><li>Gerard, M. J., Jones, S. K., Smith, L. A., Thomas, R. E., Wang, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+ergonomic+evaluation+of+the+Kinesis+ergonomic+computer+keyboard.">An ergonomic evaluation of the Kinesis ergonomic computer keyboard.</a> Ergonomics. 37 (10), 1661-1668 (1994).</li><li>Van Galen, G. P., Liesker, H., Haan, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+a+vertical+keyboard+design+on+typing+performance,+user+comfort+and+muscle+tension.">Effects of a vertical keyboard design on typing performance, user comfort and muscle tension.</a> Applied Ergonomics. 38 (1), 99-107 (2007).</li><li>Baker, N. A., Cham, R., Cidboy, E. H., Cook, J., Redfern, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinematics+of+the+fingers+and+hands+during+computer+keyboard+use.">Kinematics of the fingers and hands during computer keyboard use.</a> Clinical Biomechanics. 22 (1), 34-43 (2007).</li><li>Soukoref, R. W., MacKenzie, I. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metrics+for+text+input+research:+an+evaluation+of+MSD+and+KSPC,+and+a+new+unified+error+metric.">Metrics for text input research: an evaluation of MSD and KSPC, and a new unified error metric.</a> Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , 113-120 (2003).</li><li>Mackenzie, I. S., Soukoreff, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phrase+sets+for+evaluating+text+entry+techniques.">Phrase sets for evaluating text entry techniques.</a> CHI'03 Extended Abstracts on Human Factors in Computing Systems. , 754-755 (2003).</li><li>Trudeau, M. B., Sunderland, E. M., Jindrich, D. L., Dennerlein, J. T., Federici, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+data-driven+design+evaluation+tool+for+handheld+device+soft+keyboards.">A data-driven design evaluation tool for handheld device soft keyboards.</a> Plos One. 9 (9), 107070 (2014).</li><li>Cao, S., Ho, A., He, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+and+predicting+mobile+phone+touchscreen+transcription+typing+using+an+integrated+cognitive+architecture.">Modeling and predicting mobile phone touchscreen transcription typing using an integrated cognitive architecture.</a> International Journal of Human-Computer Interaction. 34 (4-6), 544-556 (2018).</li></ol>

提交人声明没有财务披露或利益冲突。

在这项研究中，基于屏幕技术的发展，我们提出了一个总结和通用的键盘设计评估方案，以系统，准确地评估键盘设计。先前研究中的现有指标和方法，由英文字符匹配的对以及两个键之间的过渡时间被集成和修改以生成有效的协议。
在此协议中需要注意几个关键点。变量和指标的选择至关重要，因为它们决定了分析的视角，并且可以在键盘设计评估实验的后期阶段使用它?...

An erratum was issued for:&#160;<a href="https://www.jove.com/t/61796">An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones</a>. The Authors section was&#160;updated.
Yincheng Wang1 
Ke Wang1 
Yuqi Huang1 
Di Wu2 
Jian Wu3 
Jibo He4,1 
1Department of Psychology, School of Social Sciences, Tsinghua University 
2Department of Computer Science, Beijing Normal University 
3Haier Innovation Design Center, Haier Company 
4Key Laboratory of Emotion and Mental Health in Chongqing, User Experience and Human-computer Interaction Technology Institute, Chongqing University of Arts and Sciences
to:
Yincheng Wang1 
Ke Wang1 
Yuqi Huang1 
Di Wu2 
Jian Wu3 
Jibo He1 
1Department of Psychology, School of Social Sciences, Tsinghua University 
2Department of Computer Science, Beijing Normal University 
3Haier Innovation Design Center, Haier Company

An erratum was issued for:&#160;<a href="https://www.jove.com/t/61796">An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones</a>. The Authors section was&#160;updated.

Erratum: An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones

键盘输入是人机交互的主流方式1，2，随着智能手机的普及，键盘输入获得了数十亿用户。2019年，全球智能手机普及率已达41.5%3，而美国是普及率最高的国家，则高达79.1%4 。截至2020年第一季度，搜狗手机键盘日活跃用户约4.8亿5.截至2020年5月6日，谷歌Gboard的下载量已超过10亿次6。
不令人满意的键盘输入体验随着手机屏幕的放大而增加。虽然放大后的屏幕旨在改善观看体验，但它改变了智能手机的重力、尺寸和重量，导致用户反复改变握持姿势以到达偏远地区（例如，右撇子用户的按钮A和Q），从而导致输入效率低下。肌肉拉伸可能导致使用者患有肌肉骨骼疾病，手部疼痛和不同类型的疾病（例如，腕管综合征，拇指骨关节炎和拇指腱鞘炎7，8，9，10）。喜欢单手使用的用户条件更差11，12.
因此，键盘设计的评估和优化已成为心理学、技术和人体工程学研究的热点。输入法编辑器（IME）公司和研究人员不断提出可变键盘设计和概念，以优化输入体验和效率，包括布局更改和字符重新排序的键盘：Microsoft WordFlow Keyboard13，Gloryof Kings14中的功能按钮区域，IJQWERTY15和Quasi-QWERTY16。
现有的键盘设计评估方法因研究者而异，除了几个高度接受的指标外，提出了更准确的指标。然而，对于各种指标，没有提供一个总结和系统的协议来演示评估和分析键盘设计的过程。菲茨定律17及其扩展版FFitts定律18描述了人机交互，被广泛采用来评估键盘性能19，20，21，22。此外，提出了拇指的功能区域以改善键盘设计，并且它描述了一个弯曲的运动区域，以便拇指舒适地完成输入任务23。基于这些理论，包括每分钟单词数，单词错误率和主观反馈（感知可用性，感知性能，感知速度，主观工作量，感知的劳累和疼痛以及使用意图等）在内的指标被高度采用，在以前的研究中部分使用24，25，26，27，28，29 除了建模和模拟方法。此外，近年来还使用了每个按钮上接触点的拟合椭圆及其偏移量30，31来研究输入事件的准确性能。此外，还采用皮肤电反应、心率、肌电活动、手势和身体运动32、33、34、35等方式直接或间接评价用户的肌肉疲劳、舒适度和满意度。然而，这些不同的方法缺乏对所用指标的适当性的反思，新手研究人员可能会混淆为他或她的研究选择适当的指标。
关于键盘设计的研究也很容易进行，操作和分析。随着屏幕技术的蓬勃发展，可以很容易地收集更多的行为数据来深入评估键盘设计（例如，两个键之间的转换时间和每个接触点的坐标数据）。基于上述数据，研究人员可以精确地探索键盘设计的细节，并分析其缺点和优点。与其他人机交互研究相比，便携式智能手机键盘设计的研究也具有很高的应用价值，因为其庞大的用户群不需要昂贵的设备，复杂的材料或巨大的实验室空间。关于研究的问卷，量表和Python脚本是开源的，易于访问。
本研究的目的是总结以前的方法，以展示一种系统，精确和通用的协议来评估和分析智能手机上的键盘设计。示例实验和结果旨在展示与传统QWERTY键盘相比，带有大小可调按钮的曲面QWERTY键盘是否可以优化5英寸智能手机上单手输入的输入体验，并分享数据分析的可视化方法和Python脚本。

<table>
	<tbody>
		<tr>
			<td>Changxiang 6S smartphone</td>
			<td>Huawei</td>
			<td></td>
			<td>Smartphone used in the examplar study</td>
		</tr>
		<tr>
			<td>Curved QWERTY keyboard software</td>
			<td>Tsinghua University</td>
			<td></td>
			<td>Developed by authors</td>
		</tr>
		<tr>
			<td>SPSS software</td>
			<td>IBM</td>
			<td></td>
			<td>Data analysis software</td>
		</tr>
		<tr>
			<td>G*Power software</td>
			<td>Heinrich-Heine-Universit&#228;t D&#252;sseldorf</td>
			<td></td>
			<td>Sample size calculation</td>
		</tr>
		<tr>
			<td>E4 portable wireless wristband</td>
			<td>Empatica</td>
			<td></td>
			<td>Recording galvanic skin response and heart rate</td>
		</tr>
		<tr>
			<td>Arqus</td>
			<td>Qualysis</td>
			<td></td>
			<td>Motion capture camera platform</td>
		</tr>
		<tr>
			<td>Passive marker</td>
			<td>Qualysis</td>
			<td></td>
			<td>Appropriate sizes: 2.5 mm, 4 mm, and 6.5 mm</td>
		</tr>
		<tr>
			<td>Trigno sEMG</td>
			<td>Delsys</td>
			<td></td>
			<td>Recording electromyographic activity</td>
		</tr>
		<tr>
			<td>Visual Studio Code</td>
			<td>Microsoft</td>
			<td></td>
			<td>Python editor</td>
		</tr>
	</tbody>
</table>

an assessment method and toolkit to evaluate keyboard design on smartphones

键盘输入在与广大用户群的人机交互中发挥了至关重要的作用，键盘设计一直是智能设备研究的基本对象之一。随着屏幕技术的发展，智能手机可以收集更精确的数据和指示器，以深入评估键盘设计。手机屏幕的放大导致了不尽如人意的输入体验和手指疼痛，特别是对于单手输入。输入效率和舒适性引起了研究人员和设计师的注意，并提出了带有尺寸可调按钮的曲面键盘，大致符合拇指的生理结构，以优化大屏幕智能手机上的单手使用。然而，它的实际影响仍然模糊不清。因此，该协议展示了一种通用的总结方法，通过自主开发的软件评估曲面QWERTY键盘设计在5英寸智能手机上的效果，该软件具有详细的变量，包括客观行为数据，主观反馈以及每个接触点的坐标数据。关于评估虚拟键盘的现有文献足够多;然而，其中只有少数几个系统地总结了评估方法和过程并进行了反思。因此，该协议填补了这一空白，并提出了一种系统评估键盘设计的过程和方法，以及用于分析和可视化的可用代码。它不需要额外或昂贵的设备，并且易于进行和操作。此外，该协议还有助于获得设计缺点的潜在原因，并启发设计的优化。总之，这种具有开源资源的协议不仅可以成为一种课堂演示实验，以激励新手开始学习，而且还有助于改善用户体验和输入法编辑器公司的收入。

代表性研究主要遵循上述方案。该研究采用2（键盘布局：弯曲QWERTY与传统QWERTY）×2（按钮尺寸：大，6.3 mm×9 mm与小，4.9 mm×7 mm）受试者内部设计，通过我们自主开发的软件，通过字符对输入任务，评估与传统QWERTY相比，弯曲的QWERTY是否可以提高输入效率和舒适度（图3).本研究没有采用昂贵的生理检测设备或动作捕捉系统，数据分析也不包含建模或模拟。
<p class="jove_content...

Watch this Scientific Journal Video about An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones at JoVE.com

An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones

所提出的协议集成了各种评估方法，并演示了一种评估智能手机键盘设计的方法。建议将英文字符匹配的对作为输入材料，并将两个键之间的过渡时间用作因变量。

一种评估智能手机键盘设计的评估方法和工具包

Keyboard input has played an essential role in human-computer interaction with a vast user base, and the keyboard design has always been one of the ...

an-assessment-method-toolkit-to-evaluate-keyboard-design-on

Research

JoVE Journal

Behavior

3.1K 次观看.  Tsinghua University. 所提出的协议集成了各种评估方法，并演示了一种评估智能手机键盘设计的方法。建议将英文字符匹配的对作为输入材料，并将两个键之间的过渡时间用作因变量。

视频: An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing methods are not sufficient as they lack reliability and validity. To approach this problem, recent research focuses on an objective pain assessment facilitated by parameters of responses derived from physiology, and video and audio signals. To develop reliable automated pain recognition systems, efforts have been made in creating multimodal databases in order to analyze pain and detect valid pain patterns. While the results are promising, they only focus on discriminating pain or pain intensities versus no pain. In order to advance this, research should also consider the quality and duration of pain as they provide additional valuable information for more advanced pain management. To complement existing databases and the analysis of pain regarding quality and length, this paper proposes a psychophysiological experiment to elicit, measure, and collect valid pain reactions. Participants are subjected to painful stimuli that differ in intensity (low, medium, and high), duration (5 s / 1 min), and modality (heat / electric pain) while audio, video (e.g., facial expressions, body gestures, facial skin temperature), and physiological signals (e.g., electrocardiogram [ECG], skin conductance level [SCL], facial electromyography [EMG], and EMG of M. trapezius) are being recorded. The study consists of a calibration phase to determine a subject&#8217;s individual pain range (from low to intolerable pain) and a stimulation phase in which pain stimuli, depending on the calibrated range, are applied. The obtained data may allow refining, improving, and evaluating automated recognition systems in terms of an objective pain assessment. For further development of such systems and to investigate pain reactions in more detail, additional pain modalities such as pressure, chemical, or cold pain should be included in future studies. Recorded data of this study will be released as the &#8220;X-ITE Pain Database&#8221;.

This article focuses on the experimental elicitation of pain through heat (thermal) and electrical stimulation while recording physiological, visual, and paralinguistic responses. It aims at collecting valid multimodal data for analyzing pain based on its intensity, quality, and duration.&#160;

分析疼痛对热和电刺激反应的多模态信号

The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing ...

科研

行为学

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Common MCI tests are time-consuming such that indiscriminate massive screening would not be cost-effective. Here, we describe a protocol that uses machine learning techniques to rapidly select candidates for further screening via a question-based MCI test. This minimizes the number of resources required for screening because only patients who are potentially MCI positive are tested further.
This methodology was applied in an initial MCI research study that formed the starting point for the design of a selective screening decision tree. The initial study collected many demographic and lifestyle variables as well as details about patient medications. The Short Portable Mental Status Questionnaire (SPMSQ) and the Mini-Mental State Examination (MMSE) were used to detect possible cases of MCI. Finally, we used this method to design an efficient process for classifying individuals at risk of MCI. This work also provides insights into lifestyle-related factors associated with MCI that could be leveraged in the prevention and early detection of MCI among elderly populations.

This methodology produces decision trees that target population groups more prone to suffering from mild cognitive impairment and are useful for cost-effective selective screening of the disease.

设计轻度认知障碍有效选择性筛查的机器学习方法

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Common ...

Using Looming Visual Stimuli to Evaluate Mouse Vision

The visual system in the central nervous system processes diverse visual signals. Although the overall structure has been characterized from the retina through the lateral geniculate nucleus to the visual cortex, the system is complex. Cellular and molecular studies have been conducted to elucidate the mechanisms underpinning visual processing and, by extension, disease mechanisms. These studies may contribute to the development of artificial visual systems. To validate the results of these studies, behavioral vision testing is necessary. Here, we show that the looming stimulation experiment is a reliable mouse vision test that requires a relatively simple setup. The looming experiment was conducted in a large enclosure with a shelter in one corner and a computer monitor located on the ceiling. A CCD camera positioned next to the computer monitor served to observe mouse behavior. A mouse was placed in the enclosure for 10 minutes and allowed to acclimate to and explore the surroundings. Then, the monitor projected a program-derived looming stimulus 10 times. The mouse responded to the stimuli either by freezing or by fleeing to the hiding place. The mouse&#39;s behavior before and after the looming stimuli was recorded, and the video was analyzed using motion tracking software. The velocity of the mouse movement significantly changed after the looming stimuli. In contrast, no reaction was observed in blind mice. Our results demonstrate that the simple looming experiment is a reliable test of mouse vision.

To examine mouse vision, we conducted a looming test. Mice were placed in a large square arena with a monitor on its ceiling. The looming visual stimulus consistently evoked freezing or flight reactions in the mice.

利用视觉刺激技术评价小鼠视力

The visual system in the central nervous system processes diverse visual signals. Although the overall structure has been characterized from the retina ...

Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace

Reaching and grasping are highly-coupled movements, and their underlying neural dynamics have been widely studied in the last decade. To distinguish reaching and grasping encodings, it is essential to present different object identities independent of their positions. Presented here is the design of an automatic apparatus that is assembled with a turning table and three-dimensional (3D) translational device to achieve this goal. The turning table switches different objects corresponding to different grip types while the 3D translational device transports the turning table in 3D space. Both are driven independently by motors so that the target position and object are combined arbitrarily. Meanwhile, wrist trajectory and grip types are recorded via the motion capture system and touch sensors, respectively. Furthermore, representative results that demonstrate successfully trained monkey using this system are described. It is expected that this apparatus will facilitate researchers to study kinematics, neural principles, and brain-machine interfaces related to upper limb function.

Presented here is a protocol to build an automatic apparatus that guides a monkey to perform the flexible reach-to-grasp task. The apparatus combines a 3D translational device and turning table to present multiple objects in an arbitrary position in 3D space.

设计和使用用于在 3D 工作区中呈现可抓握对象的设备

Reaching and grasping are highly-coupled movements, and their underlying neural dynamics have been widely studied in the last decade. To distinguish ...

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

As many scholars and practitioners study personalization and relationship marketing, it is important to provide personalization such as mass customization through marketing technology. The purpose of this study is to examine how to conduct consumer research using an online survey and analysis of data. This study examines consumers&#39;&#160;perceived benefits while customizing a product as well as emotional product attachment, attitudes toward a customization program, and loyalty intentions in the context of online retailing. In addition, this study investigates how consumer responses are different based on individual characteristics such as fashion innovativeness. An online survey company in South Korea recruited 290 female apparel shoppers who purchased apparel online. To enhance external validity, this study used an existing retail website with a well-established mass customization program. After completing the customization program, participants complete the online questionnaire. Structural equation modeling (SEM) and latent mean analyses (LMAs) are then performed for analyses. This study stresses the importance of testing measurement invariance for mean comparisons. Before the SEM and LMA, this study follows the hierarchy of invariance tests (configural invariance test, metric invariance test, and scalar invariance test), which are not considered by traditional approaches such as ANOVA. These statistical analyses provide applicability of the invariance test procedures and LMA to consumer behaviors. The conclusions of mean differences have integrity and validity because they are guided by a sophisticated statistical procedure to ensure measurement invariance.

Presented here is a protocol to examine consumer responses toward mass customization in the context of online retailing. The protocol details the online survey procedure and how to analyze data using structural equation modeling and group differences using latent mean analyses.

应用 eMASS 定制计划作为评估消费者权益的研究工具

As many scholars and practitioners study personalization and relationship marketing, it is important to provide personalization such as mass customization ...

Assessment of Sexual Behavior of Male Mice

Sexual behavior is highly species-specific. Although rodents have slightly different sexual behaviors, mice and rats have a similar sexual behavioral pattern. The purpose of this article is to describe the hormone-induced estrus ovariectomized female model and the experimental procedure for the assessment of sexual behavior of male mice. The most important sexual behavioral elements are demonstrated in the video and illustrations. The critical steps, advantages, and limitations of the sexual behavior test are explained as well. Finally, the behavior parameters are presented, and mounting, intromission, and ejaculation processes in mating are distinguished. Behavioral parameters are assessed in terms of the occurred duration and counts during the test period.

This article describes how to perform sexual behavior tests in male mice.

雄性小鼠性行为评估

Sexual behavior is highly species-specific. Although rodents have slightly different sexual behaviors, mice and rats have a similar sexual behavioral ...

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Current athlete monitoring practice in team sports is mainly based on positional data measured by global positioning or local positioning systems. The disadvantage of these measurement systems is that they do not register lower extremity kinematics, which could be a useful measure for identifying injury-risk factors. Rapid development in sensor technology may overcome the limitations of the current measurement systems. With inertial measurement units (IMUs) securely fixed to body segments, sensor fusion algorithms and a biomechanical model, joint kinematics could be estimated. The main purpose of this article is to demonstrate a sensor setup for estimating hip and knee joint kinematics of team sport athletes in the field. Five male subjects (age 22.5 &#177; 2.1 years; body mass 77.0 &#177; 3.8 kg; height 184.3 &#177; 5.2 cm; training experience 15.3 &#177; 4.8 years) performed a maximal 30-meter linear sprint. Hip and knee joint angles and angular velocities were obtained by five IMUs placed on the pelvis, both thighs and both shanks. Hip angles ranged from 195&#176; (&#177; 8&#176;) extension to 100.5&#176; (&#177; 8&#176;) flexion and knee angles ranged from 168.6&#176; (&#177; 12&#176;) minimal flexion and 62.8&#176; (&#177; 12&#176;) maximal flexion. Furthermore, hip angular velocity ranged between 802.6 &#176;&#183;s-1 (&#177; 192 &#176;&#183;s-1) and -674.9 &#176;&#183;s-1 (&#177; 130 &#176;&#183;s-1). Knee angular velocity ranged between 1155.9 &#176;&#183;s-1 (&#177; 200 &#176;&#183;s-1) and -1208.2 &#176;&#183;s-1 (&#177; 264 &#176;&#183;s-1). The sensor setup has been validated and could provide additional information with regard to athlete monitoring in the field.&#160;This may help professionals in a daily sports setting to evaluate their training programs, aiming to reduce injury and optimize performance.

Monitoring athletes is essential for improving performance and reducing injury risk in team sports. Current methods to monitor athletes do not include the lower extremities. Attaching multiple inertial measurement units to the lower extremities could improve monitoring athletes in the field.

一种基于惯性测量单元的方法，以评估场上团队运动运动员的臀部和膝盖关节运动学

Current athlete monitoring practice in team sports is mainly based on positional data measured by global positioning or local positioning systems. The ...

Flypub To Study Ethanol Induced Behavioral Disinhibition and Sensitization

Alcohol use disorder (AUD) remains a serious problem in our society. To develop effective interventions for addiction, it is important to understand the underlying neurobiological mechanisms, for which diverse experimental approaches and model systems are needed. The main ingredient of alcoholic beverages is ethanol, which causes adaptive changes in the central nervous system and behavior upon chronic intake. Behavioral sensitization (i.e., escalated responses) in particular represents a key adaptive change underlying addiction. Most ethanol-induced behavioral sensitization studies in animal models have been conducted on the locomotor activating effect of ethanol. A prominent effect of ethanol is behavioral disinhibition. Behavioral sensitization to the disinhibition effect of ethanol, however, is underrepresented. To address this issue, we developed the Flypub assay that allows measuring the escalated increase in disinhibited courtship activities upon recurring ethanol exposure in Drosophila melanogaster.&#160;Here, we report the step-by-step Flypub assay including assembly of ethanol exposure chambers, setup of the assay station, criteria for fly care and collection, ethanol delivery, quantification of disinhibited courtship activities, data processing and statistical analysis. Also provided are how to troubleshoot critical steps, overcome limitations and expand its utility to assess additional ethanol-induced behaviors. The Flypub assay in combination with powerful genetic tools in Drosophila melanogaster will facilitate the task of discovering the mechanism underlying ethanol-induced behavioral sensitization.

The Flypub assay measures the behaviors that the fruit fly Drosophila melanogaster displays under the influence of ethanol. The assay can be readily mastered by experimenters at all levels and applied to various vaporized stimuli, facilitating substance abuse and addiction studies.

飞行酒吧研究乙醇诱导的行为抑制和敏感性

Alcohol use disorder (AUD) remains a serious problem in our society. To develop effective interventions for addiction, it is important to understand the ...

Assessment of Stress Effects on Cognitive Flexibility using an Operant Strategy Shifting Paradigm

Stress affects cognitive function. Whether stress enhances or impairs cognitive function depends on several factors, including the 1) type, intensity, and duration of the stressor; 2) type of cognitive function under study; and 3) timing of the stressor in relation to learning or executing the cognitive task. Furthermore, sex differences among the effects of stress on cognitive function have been widely documented. Described here is an adaptation of an automated operant strategy shifting paradigm to assess how variations in stress affect cognitive flexibility in male and female Sprague Dawley rats. Specifically, restraint stress is used before or after training in this operant-based task to examine how stress affects cognitive performance in both sexes. Particular brain areas associated with each task in this automated paradigm have been well-established (i.e., the medial prefrontal cortex and orbitofrontal cortex). This allows for targeted manipulations during the experiment or the assessment of particular genes and proteins in these regions upon completion of the paradigm. This paradigm also allows for the detection of different types of performance errors that occur after stress, each of which has defined neural substrates. Also identified are distinct sex differences in perseverative errors after a repeated restraint stress paradigm. The use of these techniques in a preclinical model may reveal how stress affects the brain and impairs cognition in psychiatric disorders, such as post-traumatic stress disorder (PTSD) and major depressive disorder (MDD), which display marked sex differences in prevalence.

Stressful life events impair cognitive function, increasing the risk of psychiatric disorders. This protocol illustrates how stress affects cognitive flexibility using an automated operant strategy shifting paradigm in male and female Sprague Dawley rats. Specific brain areas underlying particular behaviors are discussed, and translational relevance of results are explored.

使用操作策略转移范式评估压力对认知灵活性的影响

Stress affects cognitive function. Whether stress enhances or impairs cognitive function depends on several factors, including the 1) type, intensity, and ...

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Collision warning system plays a key role in the prevention of driving distractions and drowsy driving. Previous studies have proven the advantages of tactile warnings in reducing driver&#8217;s brake response time. At the same time, tactile warnings have been proved effective in take-over request (TOR) for partially autonomous vehicles.
How the performance of tactile warnings can be optimized is an ongoing hot research topic in this field. Thus, the presented low-cost driving simulation software and methods are introduced to attract more researchers to take part in the investigation. The presented protocol has been divided into five sections: 1) participants, 2) driving simulation software configuration, 3) driving simulator preparation, 4) vibrating toolkit configuration and preparation, and 5) conducting the experiment.
In the exemplar study, participants wore the tactile vibrating toolkit and performed an established car-following task using the customized driving simulation software. The front vehicle braked intermittently, and vibrating warnings were delivered whenever the front vehicle was braking. Participants were instructed to respond as quickly as possible to the sudden brakes of the front vehicle. Driving dynamics, such as the brake response time and brake response rate, were recorded by the simulation software for data analysis.
The presented protocol offers insight into the exploration of the effectiveness of tactile warnings on different body locations. In addition to the car-following task that is demonstrated in the exemplar experiment, this protocol also provides options&#160;to apply other paradigms to the driving simulation studies by making simple software configuration without any code development. However, it is important to note that due to its affordable price, the driving simulation software and hardware introduced here may not be able to fully compete with other high-fidelity commercial driving simulators. Nevertheless, this protocol can act as an affordable and user-friendly alternative to the general high-fidelity commercial driving simulators.

This protocol describes a driving simulation platform and a tactile vibrating toolkit for the investigation of driving-related research. An exemplar experiment exploring the effectiveness of tactile warnings is also presented.&#160;

触觉振动工具包和驾驶模拟平台，用于驾驶相关研究

Collision warning system plays a key role in the prevention of driving distractions and drowsy driving. Previous studies have proven the advantages of ...