title: Mental workload prediction based on attentional resource allocation and information processing.
abstract: Mental workload is an important component in complex human-machine systems. The limited applicability of empirical workload measures produces the need for workload modeling and prediction methods. In the present study, a mental workload prediction model is built on the basis of attentional resource allocation and information processing to ensure pilots' accuracy and speed in understanding large amounts of flight information on the cockpit display interface. Validation with an empirical study of an abnormal attitude recovery task showed that this model's prediction of mental workload highly correlated with experimental results. This mental workload prediction model provides a new tool for optimizing human factors interface design and reducing human errors.
authors.affiliation: School of Aeronautics Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China.
authors.forename: Xu
authors.initials: X
authors.lastname: Xiao
authors.affiliation: School of Aeronautics Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China.
authors.forename: Xiaoru
authors.initials: X
authors.lastname: Wanyan
authors.affiliation: School of Aeronautics Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China.
authors.forename: Damin
authors.initials: D
authors.lastname: Zhuang
mesh_terms: D001288:Attention / Q000502:physiology*; D001359:Aviation; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D056344:Executive Function / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D008959:Models, Neurological; D011597:Psychomotor Performance / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology; D016526:Workload; D055815:Young Adult
keywords: Mental workload; attention allocation; ergonomics; information theory; prediction model