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This paper proposes a new framework for the online monitoring and adaptive control of automation in complex and safety-critical human-machine systems using psychophysiological markers relating to humans under mental stress. The starting point of this framework relates to the assessment of the so-called operator functional state using psychophysiological measures. An adaptive fuzzy model linking heart-rate...
This paper presents a new framework for studies into the on-line monitoring and adaptive control of psychophysiological markers relating to human operators working under stress. The starting point of this framework is the assessment of compromised operator functional state (OFS) using physiological and behavioral markers of strain. A fuzzy model linking Heart-Rate Variability (HRV) and Task Load Index...
This paper assesses the operator functional state (OFS) based on a collection of psychophysiological and performance measures. Two types of adaptive fuzzy models, namely ANFIS (adaptive-network-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved in an automation-enhanced cabin...
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...
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