CHS: Medium: Collaborative Research: Activity Recognition for Reducing Delays in Fast-Response Teamwork

CHS：中：协作研究：减少快速响应团队合作延迟的活动识别

• 批准号: 1763509
• 负责人: Aleksandra Sarcevic
• 金额: $ 27万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1763509&HistoricalAwards=false
• 关键词: CHS; Medium; Collaborative; Research; Activity

Human performance in time-critical teamwork settings relies on appropriate and timely task completion. Time perception, a critical cognitive function that influences team performance, is often skewed in these settings and is impacted by cognitive workload. This project will address timeliness errors by automatically and unobtrusively modeling and tracking cross-disciplinary task performance through analysis of verbal communication and the use of information artifacts. The resulting model will be used to display alerts about timeliness of critical tasks in a way that supports team members' information needs without increasing their cognitive workload. The benefits and costs of this approach will be evaluated in a simulation setting, measuring its impact on team performance and overall goal accomplishment, as well as its impact on workload and distraction. The application domain for this research is trauma resuscitation, the early evaluation and management of injured patients in the emergency department; the goal is for increased temporal awareness to improve both trauma team efficiency and patient outcomes, saving money and lives. Further, the project will provide opportunities for interdisciplinary education involving students from computer science and medicine. This project will develop techniques for monitoring the progress of teamwork and displaying alerts about timeliness of critical tasks. The key system components will include recognizing activities, modeling process deviations and delays, and displaying process information in a way that does not divert attention from the work. Novel techniques for activity recognition in fast-paced and crowded collaborative settings will be based on passive RFID, speech recognition, and computer vision, supplemented by other sensors and digital devices. The proposed research will develop (1) temporal models of verbal communication and digital document interaction during complex activities in fast-paced teamwork for the purpose of automatic activity recognition; (2) approaches for real-time recognition of over a hundred different activities in the presence of up to a thousand RFID tags; and (3) approaches for displaying delay information for rapid assimilation under high task load that learn from workers' responses to improve their usefulness to the team. Together, the work will provide building blocks for computerized support of teams not just in the trauma domain, but in other domains with complex, interleaved tasks such as surgery, traffic control, and disaster management.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在时间紧迫的团队合作环境中，人类的表现依赖于适当和及时地完成任务。时间知觉是影响团队绩效的一项关键认知功能，在这些环境中往往会出现偏差，并受到认知工作量的影响。该项目将通过对言语交流和信息人工制品的分析，自动和不引人注意地对跨学科任务执行情况进行建模和跟踪，从而解决及时性错误。生成的模型将用于显示有关关键任务的及时性的警报，以支持团队成员的信息需求，而不增加他们的认知工作量。这种方法的好处和成本将在模拟环境中进行评估，衡量其对团队绩效和总体目标实现的影响，以及对工作量和分心的影响。这项研究的应用领域是创伤复苏，即急诊科对受伤患者的早期评估和管理；目标是提高对时间的认识，以提高创伤团队的效率和患者的预后，拯救资金和生命。此外，该项目将为计算机科学和医学专业的学生提供跨学科教育的机会。该项目将开发用于监控团队工作进度和显示关键任务的及时性警报的技术。关键系统组件将包括识别活动、对流程偏差和延迟进行建模，以及以不转移工作注意力的方式显示流程信息。在快节奏和拥挤的协作环境中进行活动识别的新技术将基于无源RFID、语音识别和计算机视觉，并辅之以其他传感器和数字设备。这项拟议的研究将开发(1)快节奏团队工作中复杂活动期间言语交流和数字文档交互的时间模型，以实现自动活动识别；(2)在存在多达1000个RFID标签的情况下实时识别100多个不同活动的方法；以及(3)在高任务负荷下显示延迟信息以便快速同化的方法，该方法从工人的反应中学习，以提高他们对团队的有用性。总而言之，这项工作不仅将为创伤领域的团队提供计算机化支持，而且将为具有复杂、交错任务的其他领域的团队提供构建块，如手术、交通控制和灾难管理。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Speech-Based Model for Tracking the Progression of Activities in Extreme Action Teamwork

• DOI: 10.1145/3512920
• 发表时间: 2022-03
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Swathi Jagannath;Neha Kamireddi;K. A. Zellner;R. Burd;I. Marsic;Aleksandra Sarcevic

An Analysis of Speech during Life Saving Interventions to Inform the Design of a Computerized System for Delay Detection

救生干预期间的语音分析，为延迟检测计算机系统的设计提供信息

• 发表时间: 2023
• 期刊: AMIA Annual Symposium Proceedings
• 作者: Zellner, Katherine;Villegas, Jiorgio;Neff, Charles;Getrich-Thompson, Waverly;Burd, Randall;Marsic, Ivan;Sarcevic, Aleksandra
• 通讯作者: Sarcevic, Aleksandra

Assessing the Feasibility of Speech-Based Activity Recognition in Dynamic Medical Settings

评估动态医疗环境中基于语音的活动识别的可行性

• DOI: 10.1145/3290607.3312983
• 发表时间: 2019
• 期刊: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
• 作者: Jagannath, Swathi;Sarcevic, Aleksandra;Kamireddi, Neha;Marsic, Ivan
• 通讯作者: Marsic, Ivan

Understanding Delay Awareness and Mitigation Mechanisms through an Iterative Design and Evaluation of a Prototype Alert System for Complex Teamwork

通过迭代设计和评估复杂团队合作的原型警报系统来了解延迟意识和缓解机制

• DOI: 10.1145/3610051
• 发表时间: 2023
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Zellner, Katherine A.;Sarcevic, Aleksandra;Krensta, Megan A.;Sullivan, Travis M.;Burd, Randall S.
• 通讯作者: Burd, Randall S.

”Pop-Up Alerts are the Bane of My Existence”: Designing Alerts for Cognitive Aids Used in Time-Critical Medical Settings

– 弹出警报是我存在的祸根 –：为时间紧迫的医疗环境中使用的认知辅助工具设计警报

• DOI: 10.1145/3491101.3519669
• 发表时间: 2022
• 期刊: CHI Conference on Human Factors in Computing Systems Extended Abstracts
• 作者: Mastrianni, Angela;Cui, Hua;Sarcevic, Aleksandra
• 通讯作者: Sarcevic, Aleksandra