Adaptive Behavioral Model of the Electricity Object Management Operator for Intelligent Current Personnel Condition Monitoring Systems

Abstract

The task of ensuring the reliability of the human factor (RHF) has been singled out as one of the components of state priorities in the field of safety ensuring of electric power facilities. The relevance of solving the problem of predicting a possible change in the operator functional state (OFS) for managing such objects is substantiated. The models used in practice are usually based on the analysis of bioparameters characterizing the current state of the human cardiovascular system, such as heart rate (HR), heart rate variability (HRV), blood pressure (BP), sometimes electrocardiogram parameters (ECG), skin-galvanic reaction (SGR), photoplethysmogram (PPG). Failure to take into account the effect of fatigue accumulation in such models leads to a decrease in the accuracy of OFS possible changes prediction. An iterative behavioral model of the operator is proposed that takes into account the effect of fatigue accumulation.