A PROPOSED METHODOLOGY FOR THE PREDICTION OF MENTAL WORKLOAD, BASED ON ENGINEERING SYSTEM PARAMETERS

In the design of engineering systems, mental workload is one of the mo st important factors in the allocation of cognitive tasks. Current met hods of task allocation have criteria that are defined in only general terms and are thus not very useful in aiding detailed decision-making in system design. Whilst there are many quantitative criteria availab le to determine the physical space in human machine interaction, syste m designers really require an explicit model and specific criteria for the following identification of the mental workload imposed by the sy stem; prediction of both human and system performance; evaluation of t he alternatives of system design; and the design of system components. It is argued chat the available methods of workload or performance ar e either too domain-dependent to apply to the design of other systems, or subject-dependent and thus do not reflect the objective workload i mposed by the system. The presented research adopts a new approach to cognitive task analysis in dynamic decision-making systems. Based on t he characteristics derived from task analysis, a general conceptual mo del of the prediction of mental workload in system design is proposed. In the new model, workload is represented by a set of system paramete rs-task arrival rate, task complexity, task uncertainty, and performan ce requirements-which are considered to be the main sources of workloa d. In this context, workload becomes an objective demand of engineerin g systems, independent of any subjective factors. Whether an individua l or population is overloaded depends upon their workload threshold wi th respect to the specified task and environment. It is hoped that thi s new model, after both laboratory and industrial validation, could be used by system designers to predict the workload imposed on people by systems.