Collaborative Research: Cognitive Workload Classification in Dynamic Real-World Environments: A MagnetoCardioGraphy Approach

协作研究：动态现实环境中的认知工作负载分类：心磁图方法

• 批准号: 2320491
• 负责人: Jingzhen Yang
• 金额: $ 9.99万
• 依托单位: The Research Institute at Nationwide Children's Hospital
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2320491&HistoricalAwards=false
• 关键词: Collaborative; Research; Cognitive; Workload; Classification

Cognitive workload refers to the level of mental effort put forth by an individual in response to a cognitive task. Unfortunately, no technology currently exists that can monitor an individual’s levels of cognitive workload in real-world environments using a seamless, reliable, and low-cost approach. We propose to fill this gap by using a novel magnetocardiography (MCG) system worn upon the subject’s chest to allow the sensor to collect the magnetic fields that are naturally emanated by the heart and associated with brain activity. This science is anticipated to greatly accelerate progress in such diverse disciplines as pediatric concussion recovery, pilot training, improved user-machine interfaces, injury prevention in construction environments, increased human performance in risky missions, and improved education outcomes. In addition to advances in basic science, the proposed research is expected to be of significant interest to students and the public. Through targeting interdisciplinary education and diverse recruitment, we intend to expose new audiences to STEM concepts via workshops and family-friendly outings. The proposed MCG sensor is smartly integrated in a Cyber-Physical System (CPS) with two inter-connected loops: (a) a human-in-the-loop that addresses changes in the thresholds of different cognitive states as a function of time, and (b) a non-human-in-the-loop that adapts the system’s algorithmic and hardware components for high-accuracy classification of cognitive workload with minimum resource usage. Our goals are to: (1) Build a knowledgebase concerning the impact of hardware/algorithmic advances upon MCG sensor performance in real-world settings. (2) Explore the classification of cognitive workload from MCG data and close the loop with the wearer for dynamic calibrations that address the time-varying thresholds of cognitive states. (3) Ensure operability in dynamic real-world settings and close the loop between the cyber and physical sides for minimal resource usage. (4) Validate the CPS within the framework of measuring cognitive workload for children with concussion. Without loss of generality, we select this population given the immense clinical potential: the effects of cognitive activity on pediatric concussion recovery are currently unknown, largely due to the difficulties in quantifying cognitive activity workload.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.

认知工作量是指一个人对认知任务的精神努力水平。不幸的是，目前尚无技术可以使用无缝，可靠和低成本的方法来监测个人在现实环境中的认知工作量水平。我们建议通过使用新型的磁心电图（MCG）系统磨损对受试者的胸部磨损来填补这一空白，以使传感器能够收集由心脏自然散发并与脑活动相关的磁场。预计该科学将在小儿咨询恢复，试点培训，改善用户机器接口，预防施工环境中的伤害，在风险任务中提高人类绩效以及改善教育结果等不同学科的进步，并提高了人机界面的预防。除了基础科学的进步外，拟议的研究预计将引起学生和公众的重大兴趣。通过针对跨学科教育和潜水员的招聘，我们打算通过研讨会和家庭友好的郊游来使新受众群体接触STEM概念。提出的MCG传感器巧妙地集成在网络物理系统（CPS）中，并具有两个相互连接的循环：（a）一个人的人体，可以解决不同认知状态作为时间函数的不同认知状态的阈值的变化，并且（b）非人类的无段性能适应该系统的较高的杂物，以适应该系统的较高的杂物，以适应较高的杂物。资源使用。我们的目标是：（1）建立一个知识库，涉及硬件/算法进步对现实世界中MCG传感器性能的影响。 （2）探索MCG数据认知工作量的分类，并使用佩戴者关闭循环，以进行动态校准，以解决认知状态的时变阈值。 （3）确保在动态现实世界中进行操作，并关闭网络和物理方面之间的循环，以减少资源使用。 （4）验证CP在测量咨询儿童认知工作量的框架内。在没有失去普遍性的情况下，我们选择了巨大的临床潜力：认知活动对小儿咨询恢复的影响目前未知，这在很大程度上是由于难以量化认知活动工作负载的困难。该奖项反映了NSF的法定任务，并通过使用基金会的知识优点和广泛的效果来评估来诚实地通过评估来诚实地进行评估。