这项工作得到西班牙国家研究机构和欧洲区域发展基金 (ERDF) (TIN2016-80515-R AEI/EFRD, 欧盟) 项目的支持。

下文所述的所有方法都已得到加利西亚国家拉科鲁尼亚-拉科鲁尼亚研究伦理学委员会 (reg 代码 2017/336) 的区域政府的批准。该《议定书》是在电信工程学院的一年级学生 (维哥大学) 实施的, 既在一个舒适的实验室, 又在一个关于计算机体系结构的学士学位课程的几个讲座和练习课上进行。
1. 准备设备
<ol><li>将智能手机和 tablet 设备连接到稳定的 internet 连接。</li>
	<li>打开智能手机中的蓝牙通信。</li>
	<li>在智能手机中, 搜索相应的官方应用程序商店的手腕耐磨应用。下载并安装它。</li>
	<li>在智能手机中, 搜索 PhysiologicalSignals 应用程序以捕获生理信号。下载并安装它。 注: 目前, 该应用程序是一个 beta 版本, 并可以通过请求提供访问。</li>
	<li>在平板电脑中, 搜索 StressTest 应用程序, 用于研究实验室实验。下载并安装它。 注: 目前, 该应用程序是一个 beta 版本, 并可以通过请求提供访问。</li>
	<li>打开胶辊手腕耐磨装置, 并放置耐磨。</li>
	<li>在智能手机中, 打开正式的胶辊手腕耐磨应用。 注: 该应用程序将继续与智能手机同步可穿戴设备。在某些设备中, 需要一个电子邮件地址。</li>
	<li>在智能手机中, 打开 PhysiologicalSignals 应用程序。<ol>
<li>如果收到传感器访问请求的通知, 请接受它。</li>
		<li>检查设备。等待 PhysiologicalSignals 应用程序以绿色显示穿着字。 注: 这表明可穿戴设备已被检测到, 因此将信息从传感器传输到智能手机已启用。如果此消息在步骤1.6 中未出现重复。</li>
	</ol>
</li>
</ol>2. 实验室阶段
<ol><li>准备实验室设置。选择一个舒适和无干扰的房间, 没有分心的噪音和舒适的温度 (介于22摄氏度和26°c)。</li>
	<li>打开手腕耐磨装置, 把它放在 subject´s 的非显性手腕上, 把耳机放在学生的头上。适合佩戴紧密, 但舒适的手腕周围。</li>
	<li>将智能手机和平板电脑连接到稳定的 internet 连接, 并验证蓝牙连接是否处于活动状态。</li>
	<li>在智能手机中, 启动 PhysiologicalSignals 应用程序。<ol>
<li>等待应用程序显示单词穿着绿色。</li>
		<li>在 "左侧配置" 菜单中选择 "更改用户" 选项, 并提供将完成测试的主题的 ID, 然后单击 "保存"。</li>
	</ol>
</li>
	<li>在便携式计算机中, 访问仪表板并输入测试管理员的 ID 和密码。 注意: 当前, 对于私有和安全问题, 仅在请求下才可以访问仪表板。<ol>
<li>选择主题 ID 和主题的 "重音" 选项卡。</li>
		<li>在开始实验前, 检查生理信号的演变, 等待耐磨装置达到热稳定性。 注: 热稳定性在图中被确定为一个平台。</li>
	</ol>
</li>
	<li>在 tablet 中, 启动 StressTest 应用程序。<ol>
<li>向主题解释四实验室任务。显示在每项任务中执行的一些屏幕和操作。 注意: 这是非常重要的, 因为主题应该感到压力或放松, 根据所执行的活动, 而不是担心或担心将要发生什么。</li>
		<li>告诉学生不要把胳膊放在桌子上, 用可穿戴装置的手来进行活动。</li>
		<li>输入与步骤2.4.2 中相同的用户 ID, 然后单击箭头。</li>
	</ol>
</li>
	<li>启动视频任务并给学生完全控制。<ol>
<li>观察任务没有发生意外。</li>
		<li>完成任务后, 检查主题是否提供了感知到的压力。</li>
	</ol>
</li>
	<li>为1、2和3级连续启动 Stroop 颜色任务 (SCWT)。<ol>
<li>对于每个级别, 请观察子任务没有发生意外。</li>
		<li>当每个子任务完成后, 检查主题是否提供了感知到的压力。</li>
		<li>仅对于3级, 只有在4分钟后主题无法解决它的情况下, 通过按位于屏幕顶部的箭头来终止任务。</li>
	</ol>
</li>
	<li>启动节奏听觉序列加法测试 (PASAT)。<ol>
<li>观察任务没有发生意外。</li>
		<li>如果主题在4分钟后无法解决 PASAT 测试, 请按位于屏幕顶部的箭头终止任务。</li>
		<li>完成任务后, 检查主题是否提供了感知到的压力。</li>
	</ol>
</li>
	<li>启动换气过度测试。<ol>
<li>使用仪表板观察 HR 的演变。如果生理信号变化不明显, 要求主体逐渐增加灵感和失效率。</li>
		<li>万一这个主题感到头晕或不舒服, 停止这项任务。不管怎样, 四分钟后完成任务。</li>
		<li>完成任务后, 检查主题是否提供了感知到的压力。</li>
	</ol>
</li>
</ol>3. 课堂阶段
<ol><li>打开手腕可穿戴的设备, 并把穿戴在 subject´s 非显性手腕。适合佩戴紧密, 但舒适的手腕周围。</li>
	<li>将智能手机连接到稳定的 internet 连接, 并验证蓝牙连接是否处于活动状态。</li>
	<li>在智能手机中, 启动 PhysiologicalSignals 应用程序。<ol>
<li>等待应用程序显示单词穿着绿色。</li>
		<li>在 "配置" 菜单中选择 "更改用户" 选项, 提供将完成测试的主题的 ID, 然后单击 "保存"。</li>
	</ol>
</li>
	<li>在便携式计算机中, 访问仪表板并输入测试管理员的 ID 和密码。<ol>
<li>选择主题 ID 和主题的 "重音" 选项卡。</li>
		<li>检查生理信号的演变。</li>
	</ol>
</li>
	<li>对课堂上发生的与师生互动有关的事件进行注解。 注意: 相关信息和基本事件将被用来标记生理样本之后。例子事件是老师给学生的问题, 或者是理论解释的开始。</li>
	<li>在讲座结束时, 根据5级的规模, 要求主题在特定时间内完成有关其压力水平的问卷。</li>
</ol>4. 数据分析
<ol><li>在便携式计算机中, 访问仪表板并输入测试管理员的 ID 和密码。<ol>
<li>选择主题 ID 和主题的 "重音" 选项卡。</li>
		<li>选择课堂实验的日期。</li>
	</ol>
</li>
	<li>通过识别活动和感知的压力水平来标记主题的样本。<ol>
<li>根据开始和完成时间及其类型确定演讲室活动及其持续时间。</li>
		<li>对于每个活动, 选择一个感知的应力水平。</li>
	</ol>
</li>
	<li>对于每个主题和每个会话, 请使用带标记的示例下载该文件。 注意: 为每个学生创建一个逗号分隔值 (CSV) 文件, 每行反映生理信号的值, 其标准偏差、斜率和差异、活动类型、基于活动的应力 (即, 应力关联默认为活动) 和主体感知的压力。</li>
	<li>启动数据分析包。<ol>
<li>选择一组分类器 (如SVM、C4.5、k NN、随机林、天真贝叶斯和零 R), 并为每个会话导入所有学生的 CSV 文件。</li>
		<li>使用10倍交叉验证技术对分类器进行训练和评估。 注: 根据分析, 活动类型, 基于活动的应力或应力感知, 应选择作为依赖变量的研究。</li>
		<li>最后, 检查结果的准确性和错误率。</li>
	</ol>
</li>
</ol>

<ol>
	<li>IDC. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Forecasts Wearables Shipments to Reach 213.6 Million Units Worldwide in 2020 with Watches and Wristbands Driving Volume While Clothing and Eyewear Gain Traction. , (2016).</li><li>Piwek, L., Ellis, D. A., Andrews, S., Joinson, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+rise+of+consumer+health+wearables:promises+and+barriers.">The rise of consumer health wearables:promises and barriers.</a> PLoS Medicine. 13 (2), (2016).</li><li>Rudner, J., 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=Interrogation+of+Patient+Smartphone+Activity+Tracker+to+Assist+Arrhythmia+Management.">Interrogation of Patient Smartphone Activity Tracker to Assist Arrhythmia Management.</a> Annals of Emergency Medicine. 68 (3), 292-294 (2016).</li><li>Gao, Y., Li, H., Luo, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+empirical+study+of+wearable+technology+acceptance+in+healthcare.">An empirical study of wearable technology acceptance in healthcare.</a> Industrial Management &amp; Data Systems. 115 (9), 1704-1723 (2015).</li><li>Lukowicz, P., 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=Glass-physics:+using+google+glass+to+support+high+school+physics+experiments.">Glass-physics: using google glass to support high school physics experiments.</a> Proceedings of the 2015 ACM International Symposium on Wearable Computers - ISWC '15. , 151-154 (2015).</li><li>Sapargaliyev, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Wearables in Education: Expectations and Disappointments. , 73-78 (2015).</li><li>de Arriba P&#233;rez, F., CaeiroRodr&#237;guez, M., Santos Gago, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+do+you+sleep?+Using+off+the+shelf+wrist+wearables+to+estimate+sleep+quality,+sleepiness+level,+chronotype+and+sleep+regularity+indicators.">How do you sleep? Using off the shelf wrist wearables to estimate sleep quality, sleepiness level, chronotype and sleep regularity indicators.</a> Journal of Ambient Intelligence and Humanized Computing. , 1-21 (2017).</li><li>Espinosa, H. G., Lee, J., Keogh, J., Grigg, J., James, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+Use+of+Inertial+Sensors+in+Educational+Engagement+Activities.">On the Use of Inertial Sensors in Educational Engagement Activities.</a> Procedia Engineering. 112, 262-266 (2015).</li><li>Travers, C. J., Cooper, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> El Estre&#769;s de los profesores la presio&#769;n en la actividad docente. , (1997).</li><li>Maslach, C., Jackson, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+measurement+of+experienced+burnout.">The measurement of experienced burnout.</a> Journal of occupational Behavior. 2, 99-113 (1981).</li><li>Maslach, C., Jackson, S., Leiter, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Maslach Burnout Inventory. , (1986).</li><li>Kitsantas, A., Winsler, A., Huie, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Self-Regulation+and+Ability+Predictors+of+Academic+Success+During+College:+A+Predictive+Validity+Study.">Self-Regulation and Ability Predictors of Academic Success During College: A Predictive Validity Study.</a> Journal of Advanced Academics. 20, (2008).</li><li>Deberard, C., Scott, M., Glen, I., Spielmans, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Julka+Predictors+of+academic+achievement+and+retention+among+college+freshmen:+a+longitudinal+study.">Julka Predictors of academic achievement and retention among college freshmen: a longitudinal study.</a> College Student Journal. 381, 66-80 (2004).</li><li>Healey, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Wearable and automotive systems for affect recognition from physiology. , (2000).</li><li>Vrijkotte, T. G. M., van Doornen, L. J. P., de Geus, E. J. C. <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+Work+Stress+on+Ambulatory+Blood+Pressure,+Heart+Rate,+and+Heart+Rate+Variability.">Effects of Work Stress on Ambulatory Blood Pressure, Heart Rate, and Heart Rate Variability.</a> Hypertension. 35 (4), (2000).</li><li>Karthikeyan, P., Murugappan, M., Yaacob, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Descriptive+Analysis+of+Skin+Temperature+Variability+of+Sympathetic+Nervous+System+Activity+in+Stress.">Descriptive Analysis of Skin Temperature Variability of Sympathetic Nervous System Activity in Stress.</a> Journal of Physical Therapy Science. 24 (12), 1341-1344 (2012).</li><li>de Santos Sierra, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Design, implementation and evaluation of an unconstrained and contactless biometric system based on hand geometry and stress detection. , (2012).</li><li>Natale, V., Drejak, M., Erbacci, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+sleep+with+a+smartphone+accelerometer.">Monitoring sleep with a smartphone accelerometer.</a> Sleep and Biological Rhythms. , (2012).</li><li>Guo, F., Li, Y., Kankanhalli, M., Brown, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+evaluation+of+wearable+activity+monitoring+devices.">An evaluation of wearable activity monitoring devices.</a> Proceedings of the 1st ACM international workshop on Personal data meets distributed multimedia. , (2013).</li><li>Wallen, M. P., 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=Accuracy+of+Heart+Rate+Watches:+Implications+for+Weight+Management.">Accuracy of Heart Rate Watches: Implications for Weight Management.</a> PLOS ONE. 11 (5), e0154420 (2016).</li><li>Wang, R., 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=Accuracy+of+Wrist-Worn+Heart+Rate+Monitors.">Accuracy of Wrist-Worn Heart Rate Monitors.</a> JAMA Cardiology. 2 (1), 104 (2017).</li><li>de Arriba P&#233;rez, F., CaeiroRodr&#237;guez, M., Santos Gago, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Collection+and+Processing+of+Data+from+Wrist+Wearable+Devices+in+Heterogeneous+and+Multiple-User+Scenarios.">Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios.</a> Sensors. 16 (9), 1538 (2016).</li><li>IDC. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Wearables Aren't Dead, They're Just Shifting Focus as the Market Grows 16.9% in the Fourth Quarter, According to IDC. , (2017).</li><li>Mark, H., Ian, W., Eibe, F. <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 Mining: Practical Machine Learning Tools and Techniques. , (2011).</li><li>de Arriba P&#233;rez, F., Santos Gago, J. M., Caeiro Rodr&#237;guez, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analytics+of+biometric+data+from+wearable+devices+to+support+teaching+and+learning+activities.">Analytics of biometric data from wearable devices to support teaching and learning activities.</a> Journal of Information Systems Engineering &amp; Management. 1, 41-54 (2016).</li><li>Machine Learning Group at the University of Waikato. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Weka 3 - Data Mining with Open Source Machine Learning Software in Java. , (2018).</li><li>Zhai, J., Barreto, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stress+Detection+in+Computer+Users+Based+on+Digital+Signal+Processing+of+Noninvasive+Physiological+Variables.">Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables.</a> 2006 International Conference of the IEEE Engineering in Medicine and Biology Society. , 1355-1358 (2006).</li><li>Tombaugh, T. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comprehensive+review+of+the+Paced+Auditory+Serial+Addition+Test+(PASAT).">A comprehensive review of the Paced Auditory Serial Addition Test (PASAT).</a> Archives of Clinical Neuropsychology. 21 (1), 53-76 (2006).</li><li>Fan, Q., Wang, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+real-time+realization+of+filtering+of+speech+with+DSP+TMS320VC5416+Chip.">The real-time realization of filtering of speech with DSP TMS320VC5416 Chip.</a> 2010 International Conference on Educational and Information Technology. , (2010).</li><li>Gonz&#225;lez Barajas, J. E., Velandia C&#225;rdenas, C., Nieto Camacho, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Implementaci&#243;n+de+filtro+digital+en+tiempo+real+para+detecci&#243;n+de+la+onda+R.">Implementaci&#243;n de filtro digital en tiempo real para detecci&#243;n de la onda R.</a> Revista Tecno L&#243;gicas. 18 (34), 75-86 (2015).</li><li>Mesirov, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computer+science.+Accessible+reproducible+research.">Computer science. Accessible reproducible research.</a> Science (New York, N.Y.). 327 (5964), 415-416 (2010).</li><li>American Journal Experts. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> How to Write an Easily Reproducible Protocol. , (2018).</li></ol>

作者没有什么可透露的。

胶辊可穿戴设备是当今最受欢迎的消费电子产品之一。这些设备通常用于监视物理活动, 但它们的功能和性能可能对其他领域很感兴趣。本文讨论了利用胶辊可穿戴装置评估学习环境应力的一种协议。为了分析涉及 "服饰" 和机器学习算法的不同解决方案, 此类协议的定义尤为重要。该议定书的目的是在教育环境中使用, 在这种情况下, 对压力检测程序的验证和最终的介绍可以提供 significate 的好处。...

最先进的可穿戴技术是广泛的, 其应用环境不断扩大。我们可以在市场上找到许多不同的设备, 其中的婴儿床腕 "服饰"1, 如智能手表和智能带, 是受欢迎的运动员作为个人体能监测工具2。通过应用数据分析技术, 可以对使用这些设备获得的数据进行处理, 以提供一般物理状态、睡眠质量或恢复因子等指标。在这一领域中表现出的适用性使学术界对其可能在其他领域的应用产生了兴趣, 特别是在3、4健康领域, 尽管临床试验的严格要求限制了他们的介绍。然而, 在教育等较不苛刻的背景下, 我们可以在文献中发现, 最近的调查涉及使用不同类型的可穿戴设备, 这两者都与教学活动5、6和估计学生的某些特点如睡眠模式7, 或对学生参与不同教育活动的分析8。
在我们的例子中, 我们专注于分析胶辊手腕可穿戴装置作为收集生理信号的手段, 最终将促进压力估计, 这反过来是教育环境中的一个关键方面。压力对学术活动的发展和学生的整体表现有相关影响。例如, 压力水平与9、10、11学生的倦怠综合征的发生有直接关系, 高应力水平在大一期间尤为重要, 其中辍学率为20%30%12,13是常见的。检测和控制压力指标可以显著提高学业成绩。
使用胶辊手腕耐磨装置是合理的, 因为他们有传感器, 提供信息的生理信号, 已广泛使用的科学社区在压力评估和检测。用于此目的的文献中提到的一些信号包括心率 (HR)14、心率 varaibility15、皮肤温度 (ST)16、呼吸14和电偶皮肤反应 (GSR)17。这些信号可以通过胶辊手腕 "服饰" 收集。然而, 它们不提供与临床设备相同的性能。与设备18、19、20、21之间的传感器的准确度有差异。然而, 以前的作品18,19,20,21已经表明, 在缓慢的运动场景中, 胶辊手腕可穿戴传感器有类似于专用设备的错误模式。
本文的目的是介绍一个协议, 以评估不同的解决方案的压力估计在学生使用胶辊手腕 "服饰"。有许多安排, 可以建议评估的压力水平, 涉及使用不同的手腕耐磨设备和数据分析技术, 更具体的机器学习算法。婴儿床腕 "服饰" 的特点是其高破碎, 异构性和互操作问题22。三家公司的总市场份额几乎为 50%23, 但许多其他公司的个人市场份额较小, 累计份额高于50%。另一方面, 在异质性方面, 并非所有的 "服饰" 都有相同的数量和类型的传感器, 加速度计和 h 传感器是最常见的, ST 的和 GSR 的是只存在于5% 的设备研究。至于互操作性, 有不同的操作系统和数据收集方法彼此不兼容。至于机器学习技术, 可用于估计的压力, 从采集的数据的手腕设备, 有很多选项可用24, 包括决策树, 神经网络, 最近的邻居方法, 天真的贝叶斯分类器等总结, 对于应力估计有很多可开发的解决方案, 因此设计一个评估协议有助于不同的暂定选项之间的比较, 最终选择最适合在给定的上下文中。
为了实现该协议, 需要几个工具 (图 1)。首先, 需要一个胶辊手腕耐磨装置, 以获取生理数据。这种可穿戴的设备应该至少有 HR 监控能力, 但额外的传感器是可取的 (例如,加速度计, ST, GSR 传感器)。其次, 运行 PhysiologicalSignal 应用程序的智能手机需要收集可穿戴设备捕获的数据。第三, 运行 StressTest 应用程序的平板电脑需要进行压力感应练习 (这款智能手机可以代替平板电脑使用)。第四, 收集学生对压力感知的定性数据问卷。第五, 具有 web 服务25的服务器执行数据收集和预处理, 以及一个 web 仪表板来显示信号的演变。最后, 一个数据分析包26处理的数据收集的学生使用机器学习技术。
评估协议分为两个阶段。第一个, 实验室阶段, 是在一个舒适的房间, 在那里, 不同的压力水平 (即"放松", "集中精神" 和 "压力") 通过几个共同的压力诱导任务诱导到目标对象 (学生)。第二部分是在课堂上进行的, 它涉及学生在完成若干学术活动过程中的监控: 理论解释、个人活动、短期考试、考试等.这个协议, 主体的生理信号是通过手腕装置捕捉到的。最后, 利用机器学习算法对这些信号进行处理, 对应力水平进行估计。
在实验室阶段, StressTest 应用程序被用来诱导不同的应力水平。此应用程序指导主题完成四项不同的任务。第一个任务是创建压力分析的基线。在这项任务中, 学生展示了一个4分钟的轻松视频, 其中显示了在桥上不同的日落镜头。第二个任务是对 Stroop 颜色和 Word 测试27 (SCWT) 的改编。每隔两秒钟, 主题必须选择颜色名称的颜色 (红色、绿色、橙色、蓝色和紫色)。在屏幕底部有几个按钮, 其中包含每种颜色的初始字母, 可供主题选择每次绘制的颜色。例如, 指向蓝色的按钮描述了字母 B。在我们的例子中, 这个测试分为三不同的难度水平。对于第一级 (SCWT1), 彩色的 "颜色词" 将以与按钮相同的顺序出现, 因此颜色和名称直接匹配。此级别被视为基线, 因为它不涉及任何困难, 并且主题只应正确按下按钮, 始终按相同的顺序。对于第二级 (SCWT2), 彩色的 "颜色词" 随机出现, 但名称和颜色之间的对应关系保持不变。每当主题失败时发出蜂鸣音, 如果出现两个错误, 则将重置正确的颜色分数。最后, 最困难的级别 (SCWT3), 名称和颜色不匹配。以这种方式, 这个层次的目的是更复杂和压力的主题。第三项任务包括节奏听觉系列加法测试 (PASAT)28, 它测量学生如何体验浓度测试。在这个任务中, 一个连续数字的序列被大声地演奏, 并且学生必须增加最后两个数字并且写结果在提供的屏幕盒在听下数字之前。在这项任务中, 如果主题犯了错误, 就会发生一个令人不安的事件, 产生压力 (两个数字声音在同一时间或长时间的沉默保持)。在这种情况下, 如果提交了三错误, 将重置 sum 帐户。第四项任务是在过度通气的活动中诱导相同的变异, 在生理信号, 这将挑起紧张的情况17。在每一个任务和级别的末尾, 该主题必须根据5值的李克特量表, 使用应用程序本身来表示感知到的压力水平。
在课堂阶段, 学生与其他同学一起进行他们的普通学术活动。该议定书侧重于课堂特定活动中的压力水平。在讲座结束时, 学生完成了一份简短的问卷 (附件 1), 以表明在几项活动中, 根据5价值表所感知到的压力水平。

<table><tbody><tr><td>Microsoft Band 2</td><td>Microsoft</td><td></td><td>Wearable</td></tr><tr><td>Nexus 5</td><td>LG/Google</td><td></td><td>Smartphone</td></tr><tr><td>PhysiologicalSignals</td><td>Developed by the paper authors</td><td></td><td>App to collect data from wearables</td></tr><tr><td>StressTest</td><td>Developed by the paper authors</td><td></td><td>App to develop laboraty experiment: Video visualization, Stroop color and word test, paced auditory serial addition test (PASAT) , hyperventilation activity&amp;nbsp;</td></tr><tr><td>Quizs</td><td>Developed by the paper authors</td><td></td><td>Questionnaires to collect qualitative data on students&amp;rsquo; perception on stress</td></tr><tr><td>Server</td><td>Developed by the paper authors</td><td></td><td>Server to store, analyze and display data</td></tr><tr><td>Weka application</td><td>University of Waikato</td><td></td><td>Application to process the data using machine learning techniques</td></tr></tbody></table>

evaluation of commercial-off-the-shelf wrist wearables to estimate stress on students

可穿戴的商用现成 (胶辊) 装置在过去几年中已经流行起来, 主要是在年轻人当中进行体育活动的监测。这些设备包括传感器收集生理信号的数据, 如心率, 皮肤温度或电偶皮肤反应。通过将数据分析技术应用到这些类型的信号中, 可以得到人类行为的高层次方面的估计。在文献中, 有几项著作描述使用临床设备收集的生理数据, 以获取睡眠模式或压力的信息。然而, 使用胶辊手腕 "服饰" 采集的数据是否足以表征学习者在教育环境中的心理状态, 这仍然是一个公开的问题。本文讨论了用胶辊手腕 "服饰" 获得的数据评估应力估计的一种协议。该议定书分为两个阶段进行。第一阶段由一个受控的实验室实验组成, 其中一个移动应用程序用于通过放松的视频、Stroop 的颜色和单词测试、节奏的听觉序列加法测试和过度换气测试来诱导学生的不同的压力水平。第二阶段是在课堂上进行, 在那里进行一些学术活动的分析, 即参加理论讲座, 做练习和其他个人活动, 并进行短期测试和考试。在这两种情况下, 都考虑了从胶辊手腕 "服饰" 获得的定量数据和通过问卷收集的定性数据。该协议涉及一种简单且一致的方法, 带有压力感应应用程序和调查表, 需要支持人员的有限参与。

所讨论的议定书是在维哥大学电信工程学位第一年的计算机架构课程中实施的。这门课程有200多名学生被组织成10个工作小组。为了进行这项实验, 四组的学生应邀在学年开始时报名参加。该项目引起了学生的极大兴趣, 约有30名学生自愿参加这项研究。其中12名学生被随机挑选参加。
为我们的实验选择的胶辊手腕耐磨装置有 HR,...

Watch this Scientific Journal Video about Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students at JoVE.com

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

提出了一种基于商业现成 ("服饰") 手腕的方法来评估学生压力的方案。该协议分为两个阶段, 一是以实验室为基础的压力感应测试, 一个是在学生从事学术活动时在课堂上进行的监控阶段。

商业现成腕 "服饰" 评估学生压力的评价

Wearable commercial-off-the-shelf (COTS) devices have become popular during the last years to monitor sports activities, primarily among young people. ...

evaluation-commercial-off-shelf-wrist-wearables-to-estimate-stress-on

Research

JoVE Journal

Engineering

7.4K 次观看.  University of Vigo, Campus Lagoas-Marcosende. 提出了一种基于商业现成 ("服饰") 手腕的方法来评估学生压力的方案。该协议分为两个阶段, 一是以实验室为基础的压力感应测试, 一个是在学生从事学术活动时在课堂上进行的监控阶段。

视频: Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

An Alternative to the Traditional Cold Pressor Test: The Cold Pressor Arm Wrap

Recently research on the relationship between stress and cognition, emotion, and behavior has greatly increased. These advances have yielded insights into important questions ranging from the nature of stress&#39; influence on addiction1 to the role of stress in neural changes associated with alterations in decision-making2,3. As topics being examined by the field evolve, however, so too must the methodologies involved. In this article a practical and effective alternative to a classic stress induction technique, the cold pressor test (CPT), is presented: the cold pressor arm wrap (CPAW). CPT typically involves immersion of a participant&#39;s dominant hand in ice-cold water for a period of time4. The technique is associated with robust activation of the sympatho-adrenomedullary (SAM) axis (and release of catecholamines; e.g.&#160;adrenaline and noradrenaline) and mild-to-moderate activation of the hypothalamic-pituitary-adrenal (HPA) axis with associated glucocorticoid (e.g.&#160;cortisol) release. While CPT has been used in a wide range of studies, it can be impractical to apply in some research environments. For example use of water during, rather than prior to, magnetic resonance imaging (MRI) has the potential to damage sensitive and expensive equipment or interfere with acquisition of MRI signal. The CPAW is a practical and effective alternative to the traditional CPT. Composed of a versatile list of inexpensive and easily acquired components, CPAW makes use of MRI-safe gelpacs cooled to a temperature similar to CPT rather than actual water. Importantly CPAW is associated with levels of SAM and HPA activation comparable to CPT, and can easily be applied in a variety of research contexts. While it is important to maintain specific safety protocols when using the technique, these are easy to implement if planned for. Creation and use of the CPAW will be discussed.

The cold pressor test is a classic stress induction task used in a wide range of research examining the relationship between stress and cognition, emotion, and behavior. In this article, a practical and versatile alternative to the traditional cold pressor test is presented: the cold pressor arm wrap.

传统冷压机测试的替代方案：冷压机臂包装

Recently research on the relationship between stress and cognition, emotion, and behavior has greatly increased. These advances have yielded insights into ...

科研

行为学

Use of Galvanic Skin Responses, Salivary Biomarkers, and Self-reports to Assess Undergraduate Student Performance During a Laboratory Exam Activity

Typically, self-reports are used in educational research to assess student response and performance to a classroom activity. Yet, addition of biological and physiological measures such as salivary biomarkers and galvanic skin responses are rarely included, limiting the wealth of information that can be obtained to better understand student performance. A laboratory protocol to study undergraduate students&#39; responses to classroom events (e.g., exams) is presented. Participants were asked to complete a representative exam for their degree. Before and after the laboratory exam session, students completed an academic achievement emotions self-report and an interview that paralleled these questions when participants wore a galvanic skin sensor and salivary biomarkers were collected. Data collected from the three methods resulted in greater depth of information about students&#39; performance when compared to the self-report. The work can expand educational research capabilities through more comprehensive methods for obtaining nearer to real-time student responses to an examination activity.

Research on undergraduate students' academic achievement emotions have primarily relied on self-reports in laboratory settings. Studies rarely include bio-physiological measures to these self-reports. This protocol will describe a methodology that integrates self-reports with and bio-physiological measures to assess student response and performance during a laboratory examination activity.

皮肤电反应，唾液生物标志物和自我报告的用来评估本科生性能在一个实验室考试活动

Typically, self-reports are used in educational research to assess student response and performance to a classroom activity. Yet, addition of biological ...

Reducing State Anxiety Using Working Memory Maintenance

The purpose of this protocol is to explain how to examine the relationship between working memory processes and anxiety by combining the Sternberg Working Memory (WM) and the threat of shock paradigms. In the Sternberg WM paradigm, subjects are required to maintain a series of letters in the WM for a brief interval and respond by identifying whether the position of a given letter in the series matches a numerical prompt. In the threat of shock paradigm, subjects are exposed to alternating blocks where they are either at risk of receiving unpredictable presentations of a mild electric shock or are safe from the shock. Anxiety is probed throughout the safe and threat blocks using the acoustic startle reflex, which is potentiated under threat (Anxiety-Potentiated Startle (APS)). By conducting the Sternberg WM paradigm during the threat of shock and probing the startle response during either the WM maintenance interval or the intertrial interval, it is possible to determine the effect of WM maintenance on APS.

This protocol demonstrates how to measure anxiety-potentiated startle during the Sternberg Working Memory paradigm.

使用工作记忆维护降低状态焦虑

The purpose of this protocol is to explain how to examine the relationship between working memory processes and anxiety by combining the Sternberg Working ...

A Community-based Stress Management Program: Using Wearable Devices to Assess Whole Body Physiological Responses in Non-laboratory Settings

A pragmatic breath-based intervention to benefit human performance and stress management is timely and valuable to individuals seeking holistic approaches for emotional regulation and optimizing compensatory reserve mechanisms. This protocol is designed to not only teach mind-body awareness but also to provide feedback utilizing physiological data and survey results. The primary findings of this study showed that heart coherence and alpha variables were significantly correlated after four weeks of the breath-based meditation stress protocol. Meditation and rhythmic breathing produced significant increases in alpha brain activity. These brain physiological responses conformed to the Pleth Variability Index (PVI) changes, suggesting the ability of the human body to enter into a meditative state and effectively manage stress. When assessed after four weeks of daily practicing the techniques employed in the stress management protocol, based on the Five Facet Mindfulness Questionnaire, subjects improved in applying mindfulness skills. The overall mindfulness score, Pleth variability index (PVI), and perfusion index (PI) increased after the 4-week intervention period. Results from electroencephalography (brain waves) were consistent with a meditative state during the post-study follow-up session. This provides evidence that wearable devices are feasible for data collection during a breath-based stress management intervention. This protocol can be easily and efficiently implemented into any study design in which physiological data are desired in a non-laboratory-based setting.

Stress is an unavoidable and persistent component of life and holistic approaches for its management are being considered. A standardized methodology was created to demonstrate the feasibility of a breath-based stress management protocol that can be used with commercially available portable technology.

基于社区的压力管理计划: 在非实验室环境中使用可穿戴设备评估全身生理反应

A pragmatic breath-based intervention to benefit human performance and stress management is timely and valuable to individuals seeking holistic approaches ...

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

The current protocol aims to showcase the technology integration, providing a detailed description of adopting the HealthCloud app, developed by the Healthy Landscape and Healthy People Lab, National Taiwan University (HLHP-NTU), on smartphones and smartwatches to collect data on users' real-time psychological and physiological responses and environmental information. A flexible and integrated research method was proposed because it can be difficult to measure multi-dimensional aspects of personal data in on-site studies in landscape and outdoor recreation research. An on-site study conducted in 2020 at the National Taiwan University campus was used as an application example. A dataset of 385 participants was used after excluding invalid samples. During the experiment, participants were asked to walk around campus for 30 min when their heart rate and psychological-scale items were measured, together with several environmental metrics. This work aimed to provide a possible solution to help on-site studies track real-time human responses that match ambient factors. Due to the app's flexibility, its use on wearable devices shows excellent potential for multidisciplinary research studies.

The present protocol introduces a non-commercial self-developed application for collecting real-time on-site data, including psychological scales, GPS location, heart rate, and blood-oxygen saturation level, as well as the application's operating procedures. An empirical study conducted in Taiwan in 2020 was used as an application example.

与可穿戴设备配对以监控个人健康状况的应用程序

The current protocol aims to showcase the technology integration, providing a detailed description of adopting the HealthCloud app, developed by the ...

环境科学

Psychophysiological Stress Assessment Using Biofeedback 

In the last half century, research in biofeedback has shown the extent to which the human mind can influence the functioning of the autonomic nervous system, previously thought to be outside of conscious control. By letting people observe signals from their own bodies, biofeedback enables them to develop greater awareness of their physiological and psychological reactions, such as stress, and to learn to modify these reactions. Biofeedback practitioners can facilitate this process by assessing people s reactions to mildly stressful events and formulating a biofeedback-based treatment plan. During stress assessment the practitioner first records a baseline for physiological readings, and then presents the client with several mild stressors, such as a cognitive, physical and emotional stressor. Variety of stressors is presented in order to determine a person's stimulus-response specificity, or differences in each person's reaction to qualitatively different stimuli. This video will demonstrate the process of psychophysiological stress assessment using biofeedback and present general guidelines for treatment planning.

Psychophysiological Stress Assessment Using Biofeedback

In this video we will describe one method of assessing person's psychophysiological reaction to stress using biofeedback. We will also present general guidelines for treatment planning.

使用生物反馈的心理生理压力评估

In the last half century, research in biofeedback has shown the extent to which the human mind can influence the functioning of the autonomic nervous ...

生物学

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Over the past ten years, research into students&#39; emotions in educational environments has increased. Although researchers have called for more studies that rely on objective measures of emotional experience, limitations on utilizing multi-modal data sources exist. Studies of emotion and emotional regulation in classrooms traditionally rely on survey instruments, experience-sampling, artifacts, interviews, or observational procedures. These methods, while valuable, are mainly&#160;dependent on participant or observer subjectivity and is limited in its authentic measurement of students&#39; real-time performance to a classroom activity or task. The latter, in particular, poses a stumbling block to many scholars seeking to objectively measure emotions and other related measures in the classroom, in real-time.
The purpose of this work is to present a protocol to experimentally study students&#39; real-time responses to exam experiences during an authentic assessment situation. For this, a team of educational psychologists, engineers, and engineering education researchers designed an experimental protocol that retained the limits required for accurate physiological sensor measurement, best-practices of salivary collection, and an authentic testing environment. In particular, existing studies that rely on physiological sensors are conducted in experimental environments that are disconnected from educational settings (e.g., Trier Stress Test), detached in time (e.g., before or after a task), or introduce analysis error (e.g., use of sensors in environments where students are likely to move). This limits our understanding of students&#39; real-time responses to classroom activities and tasks. Furthermore, recent research has called for more considerations to be covered around issues of recruitment, replicability, validity, setups, data cleaning, preliminary analysis, and particular&#160;circumstances (e.g., adding a variable in the experimental design) in academic emotions research that relies on multi-modal approaches.

An experimental design was developed to investigate the real-time influences of an examination experience to assess the emotional realities students experience in higher education settings and tasks. This design is the result of a cross-disciplinary (e.g., educational psychology, biology, physiology, engineering) and multi-modal (e.g., salivary markers, surveys, electrodermal sensor) approach.

用于研究近实时真实考试体验的跨学科、多模式实验设计

Over the past ten years, research into students&#39; emotions in educational environments has increased. Although researchers have called for more studies ...

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

In medicine or industry, the analysis of high-dimensional data sets is increasingly required. However, available technical solutions are often complex to use. Therefore, new approaches like immersive analytics are welcome. Immersive analytics promise to experience high-dimensional data sets in a convenient manner for various user groups and data sets. Technically, virtual-reality devices are used to enable immersive analytics. In Industry 4.0, for example, scenarios like the identification of outliers or anomalies in high-dimensional data sets are pursued goals of immersive analytics. In this context, two important questions should be addressed for any developed technical solution on immersive analytics: First, is the technical solutions being helpful or not? Second, is the bodily experience of the technical solution positive or negative? The first question aims at the general feasibility of a technical solution, while the second one aims at the wearing comfort. Extant studies and protocols, which systematically address these questions are still rare. In this work, a study protocol is presented, which mainly investigates the usability for immersive analytics in Industry 4.0 scenarios. Specifically, the protocol is based on four pillars. First, it categorizes users based on previous experiences. Second, tasks are presented, which can be used to evaluate the feasibility of the technical solution. Third, measures are presented, which quantify the learning effect of a user. Fourth, a questionnaire&#160;evaluates the stress level when performing tasks. Based on these pillars, a technical setting was implemented that uses mixed reality smartglasses to apply the study protocol. The results of the conducted study show the applicability of the protocol on the one hand and the feasibility of immersive analytics in Industry 4.0 scenarios on the other. The presented protocol includes a discussion of discovered limitations.

This protocol delineates the technical setting of a developed mixed reality application that is used for immersive analytics. Based on this, measures are presented, which were used in a study to gain insights into usability aspects of the developed technical solution.

评估工业 4.0 方案中沉浸式分析的混合现实解决方案的可用性方面

In medicine or industry, the analysis of high-dimensional data sets is increasingly required. However, available technical solutions are often complex to ...

工程学

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Wearable sensors, which are often embedded in commercial smartwatches, allow for continuous and non-invasive health measurements and exposure assessments in clinical studies. Nevertheless, the real-life application of these technologies in studies involving a large number of participants for a significant observation period may be hindered by several practical challenges. 
In this study, we present a modified protocol from a previous intervention study for the mitigation of health effects from desert dust storms. The study involved two distinct population groups: asthmatic children aged 6-11 years and elderly patients with atrial fibrillation (AF). Both groups were equipped with a smartwatch for the assessment of physical activity (using a heart rate monitor, pedometer, and accelerometer) and location (using GPS signals to locate individuals in indoor "at home" or outdoor microenvironments). The participants were required to wear the smartwatch equipped with a data collection application on a daily basis, and data were transmitted via a wireless network to a centrally administered data collection platform for the near real-time assessment of compliance. 
Over a period of 26 months, more than 250 children and 50 patients with AF participated in the aforementioned study. The main technical challenges identified included restricting access to standard smartwatch features, such as gaming, internet browser, camera, and audio recording applications, technical issues, such as loss of GPS signal, especially in indoor environments, and the internal smartwatch settings interfering with the data collection application.
The aim of this protocol is to demonstrate how the use of publicly available application lockers and device automation applications made it possible to address most of these challenges in a simple and cost-effective way. In addition, the inclusion of a Wi-Fi received signal strength indicator significantly improved indoor localization and largely minimized GPS signal misclassification. The implementation of these protocols during the roll-out of this intervention study in the spring of 2020 led to significantly improved results in terms of data completeness and data quality.

Commercial smartwatches equipped with wearable sensors are increasingly being used in population studies. However, their utility is often constrained by their limited battery duration, memory capacity, and data quality. This report provides examples of cost-effective solutions to real-life technical challenges encountered during studies involving asthmatic children and elderly cardiac patients.

在人口研究中设置用于暴露和健康监测的消费者可穿戴设备

Wearable sensors, which are often embedded in commercial smartwatches, allow for continuous and non-invasive health measurements and exposure assessments ...

生物工程

Evaluation of Hydration Status by Bioelectrical Impedance Vector Analysis in Patients with Ischemic Heart Disease Undergoing Exercise Stress Test

Ischemic heart disease (IHD) represents a group of clinical syndromes characterized by myocardial ischemia, leading to an impairment in the myocardial blood supply and compromised perfusion. Several clinical variables assessed through a stress test, such as oxygen uptake (VO2) and heart rate oxygen pulse (HR/O2), have been attributed as cardiopulmonary prognostic factors in patients with IHD. However, other factors like hydration status (HS), potentially affecting the cardiopulmonary response, have been barely addressed. Unbalanced HS has a short-term effect on plasma volume and the sympathetic nervous system, which impacts blood volume, and lowers VO2 and HR/O2. Recently, bioelectrical impedance analysis (BIA), a method based on the opposition of body tissues (including fluid volume) to a low electrical current, has been widely used to assess HS by obtaining two components: resistance (R) and reactance (Xc) and using prediction formulas. However, several limitations as chronic illness or abnormal fluid status, may affect the results. In this sense, alternative BIA methods, such as bioelectrical impedance vector analysis (BIVA), have become relevant. R and Xc (adjusted by height) result in a vector plotted on the R/Xc graph, which allows interpreting the HS as normal or abnormal according to the distance of the mean vector. This study aims to describe how to determine HS by BIVA using a single-frequency device and compare the results with the cardiopulmonary response in patients with IHD.

Hydration status imbalances can have a short-term effect on direct and indirect determinants of oxygen uptake and pulse, and morbidity and mortality prognostic factors in ischemic heart disease. This protocol describes the technique for assessment of hydration status through bioelectrical impedance vector analysis and cardiopulmonary response during exercise stress test.

通过生物电阻抗矢量分析评估缺血性心脏病患者接受运动负荷试验的水合状态

Ischemic heart disease (IHD) represents a group of clinical syndromes characterized by myocardial ischemia, leading to an impairment in the myocardial ...