Using fault detection methods to optimize parameters in human-machine interface devices

摘要

Using methods from fault diagnosis studies and signal detection theory, an optimal model involving decision making of the human operator is formulated. Parameters are estimated based on a likelihood function methodology to characterize how human responses are elicited. The theoretical model is empirically validated with human subjects and it enables one to estimate certain properties of the human-machine interface (risk adversity).