2024/10/10 by Jiang Xu, Xu, Jiang, Qiyang Miao +12
Business, Management and Accounting · #Business Process Modeling and Analysis #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC)
paper · pdf · doi:10.48550/arxiv.2410.07804
openalex publication_date 2024/10/10 · openalex created_date 2024/10/13 · openalex updated_date 2026/07/28
This study investigates the issue of task allocation in Human-Machine Collaboration (HMC) within the context of Industry 4.0. By integrating philosophical insights and cognitive science, it clearly defines two typical modes of human behavior in human-machine interaction(HMI): skill-based intuitive behavior and knowledge-based intellectual behavior. Building on this, the concept of 'intuitive interaction flow' is innovatively introduced by combining human intuition with machine humanoid intelligence, leading to the construction of a dual-loop HMC task allocation model. Through comparative experiments measuring electroencephalogram (EEG) and electromyogram (EMG) activities, distinct physiological patterns associated with these behavior modes are identified, providing a preliminary foundation for future adaptive HMC frameworks. This work offers a pathway for developing intelligent HMC systems that effectively integrate human intuition and machine intelligence in Industry 4.0.