Towards on-line supervision and control of operational functional state (OFS) for subjects under mental stress

In safety-critical human-machine systems the operator continually adapts to new and unforeseen changes in the dynamic process and determines what actions are required to prevent or correct for drifts or faults. For a period before breakdown occurs, the operator is likely to be in a vulnerable state, able to manage predictable demands but not unexpected or difficult problems. This situation may bring potential catastrophes to the dynamic process, and the control tasks should be immediately taken over by an adaptive automation system. Thus, a real-time system for adaptive control of automation based on markers of high risk operational state of simulated process control environments is developed in this study. The developed real-time system provides a platform for research into adaptive automation through integrating a distributed process simulator and a psychophysiological signal logger.