Biometric approaches to inferring pilot trainee's affective and cognitive states

推断飞行员受训者的情感和认知状态的生物识别方法

• 批准号: 514052-2017
• 负责人: Zeng, Yong
• 金额: $ 14.5万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=669635
• 关键词: Biometric; approaches; inferring; pilot; trainee

Flight safety requires effective pilot training, which aims to equip pilot trainees with the capabilities to make correct decisions in different flight scenarios. The effectiveness of pilot training depends largely on an instructor's ability to maintain a detailed awareness of the training situation. Armed with this information, instructors can adapt a student's training to his/her specific needs in order to maximize the training benefits. This awareness relies on the quantification of pilot trainee's cognitive (thinking) and affective (emotion/feeling) states in relation to decision making and performance.**Human cognitive/affective states can be inferred from biometric data. For instance, brain waves and eye movements can measure cognitive states. Mental workload can be estimated from brain wave measurement, pupil diameter, skin conductance, cardiac measures and respiration rate. Affective state such as mental stress and other emotions can be inferred from body movements, facial expressions, and other biometric data. The objective of this proposed project is to develop biometric approaches for the quantification of pilot trainee's cognitive and affective states during the pilot training process. The deliverable from this proposed**project will be an integrated solution to quantify pilot trainee's cognitive and affective states. As a result, a novel framework will be developed to bring advanced biometric measurement technologies and algorithms from the laboratory setting into the simulator-based pilot training environment. This framework can be easily extended to other complex yet critical field applications such as medical and military mission training. This proposed project team will include three universities: Concordia University, University of Montreal, and McGill University, an national research lab: National Research Council Canada, three companies: CAE, Marivent, and GlobVision, and one research consortium: CRIAQ (Consortium for Research and Innovation in Aerospace in Québec).

飞行安全需要有效的飞行员培训，其目的是使受训飞行员具备在不同飞行情景下做出正确决策的能力。飞行员训练的有效性在很大程度上取决于教员对训练情况保持详细了解的能力。有了这些信息，教师可以调整学生的培训，以适应他/她的具体需求，以最大限度地提高培训效益。这种意识依赖于对与决策和表现有关的受训飞行员认知（思维）和情感（情绪/感觉）状态的量化。人类的认知/情感状态可以从生物特征数据中推断出来。例如，脑电波和眼球运动可以测量认知状态。脑力负荷可以通过脑电波测量、瞳孔直径、皮肤电导、心脏测量和呼吸率来估计。情感状态，如精神压力和其他情绪，可以从身体动作，面部表情和其他生物特征数据推断。本项目的目标是开发生物识别方法，用于量化飞行员受训者在飞行员培训过程中的认知和情感状态。本拟议 ** 项目的交付成果将是一个综合解决方案，以量化飞行学员的认知和情感状态。因此，将开发一个新的框架，将先进的生物特征测量技术和算法从实验室设置到基于模拟器的飞行员培训环境。这个框架可以很容易地扩展到其他复杂但关键的领域应用，如医疗和军事使命培训。这个拟议的项目小组将包括三所大学：康考迪亚大学、蒙特利尔大学和麦吉尔大学，一个国家研究实验室：加拿大国家研究理事会，三家公司：CAE、Marivent和GlobVision，以及一个研究财团：CRIAQ（魁北克航空航天研究和创新财团）。