Abstract
This paper presents a modelling design framework and results for human participants undergoing mental stress. A mental stressful scenario is achieved while participants perform operations in a simulated control process on an automation-enhanced Cabin Air Management System simulator. Recordings from a previous experiment using psychophysiological markers (Heart Rate Variability and Task Load Index) as inputs with an output performance marker (Time In Range) were used for offline modelling training and validation. Interval Type-2 Fuzzy Logic (IT2FL) architecture optimized with Genetic Algorithms and with an efficient type-reduction algorithm, was selected as the modelling technique. Results demonstrate the ability of IT2FL systems to cope with an additional level of uncertainty and to adapt to important input-output relation changes on validation of the model. These results surpass performance in validation of a type 1 Mamdani Fuzzy Logic system constructed and validated previously in a similar fashion. The constructed model provides an adequate framework that can be used for the prevention of operator breakdown.
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