A robust operators’ cognitive workload recognition method based on denoising masked autoencoder

• Main Authors: Yu, Xiaoqing, Chen, Chun-Hsien
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering; Cognitive workload; Masked autoencoder
• Online Access: https://hdl.handle.net/10356/180657
• Institution: Nanyang Technological University

Identifying the cognitive workload of operators is crucial in complex human-automation collaboration systems. An excessive workload can lead to fatigue or accidents, while an insufficient workload may diminish situational awareness and efficiency. However, existing supervised learning-based methods...