Assessing output measurement optimally in physiological system identification by a design measure approach

The design of optimal experiments in physiological system identification may be very difficult to perform or even not always required, especially in the early model building/validation phase. It is however important to understand the role that the design variables exert on the precision of parameter estimates and to have guidelines for improving the experiments. For this purpose we propose here an approach based on the Kiefer-Wolfowitz theorem for assessing the optimality of output measurements for given system/experiment models, which does not require the explicit solution of the optimal sampling schedule design problem.