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Advanced Neuro-ergonomics and Cognitive Science in Aviation

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AAE5109aaeFaculty of Engineering3 credits

Advanced Neuro-ergonomics and Cognitive Science in Aviation

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Overview

来自官方课程资料的结构化信息

Course Code

AAE5109

Course Name

Advanced Neuro-ergonomics and Cognitive Science in Aviation

Department

aae

School ID

polyu

Faculty

Faculty of Engineering

Credits

3 credits

Level

5 Pre-requisite/ Co-requisite/

课程简介

/ Indicative Syllabus Introduction: The overall thought, principles, and applications of neuro- ergonomics and cognitive science in aviation. Human Cognition in Aviation: Cognitive workload, situational awareness, fatigue, decision-making, attention, and stress of air traffic controllers and pilots. Data Analysis: Data pre-processing, cleaning, interpreting, and visualizing, and pattern recognition of neuro-psycho-physiological data. Technological Advancements in Neuro-Ergonomics: Cognitive states modelling, monitoring, prediction, neuroimaging, neurofeedback, and brain-computer interfaces. Laboratory and Case Studies: Neuro-ergonomic technologies and simulators tutorial. Human cognitive workload monitoring and situation awareness detection. -- 1 of 3 --

目标

This subject will provide students with 1. Systematically understand the core theories and methodologies of neuro-ergonomics and cognitive science in aviation. 2. Explore how to integrate cutting-edge neuro-ergonomics technologies, human factors experiments, and cognitive analysis into aviation safety. 3. Cultivate problem-solving ability grounded in cognitive science to bridge the gap from data analysis to real-world interventions in aviation safety situations.

先修要求

/ Co-requisite/ Exclusion Nil

Teaching Pattern

Methodology Teaching is conducted through class lectures, laboratory, and case studies. The basic knowledge, research methodology and theoretical models will be introduced. The understanding of how to address and identify the human factors problem and formulate the resolution will be emphasized. Research methodology, case study and analytics skills and tools (e.g., MATLAB) are taught in class as well as the related real-life scenarios to enhance the teaching and learning abilities. Teaching/Learning Methodology Outcomes a b c d Lecture     Laboratory   Case Study   