Abstract
This paper describes a real-time conditional human reliability model constructed to predict the likelihood of human performance metrics exceeding critical boundaries in a future time interval. The model is implemented by collecting real-time data from selected performance measures, modeling and forecasting these measures, and then converting the forecast results into reliability measures. To demonstrate the feasibility of the proposed model, a prototype software package has been developed and tested for a simple movement task.
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