Robust optimal experimental design for study of the human head-neck tracking response

In an effort to better understand the human head-neck target tracking response, we have developed a procedure for designing a robustly optimal experimental configuration for system identification. This configuration is comprised of a parametrized input sequence along with physical parameters for the experi-ment. We have developed both nominal and experimental models containing uncertainties for the target tracking task based on several preliminary experimental data sets, and identified a feasible population of subject controller parameters. We applied a min-max optimization scheme to minimize a performance cost over the feasible experimental configurations, while simultaneously maximizing it over the population of subject controller pa-rameters. In this way, a minimum level of design performance for any subject within the defined population can be guaranteed. We show that in the worst-case, the performance cost is 0.473 in flexion/extension, and 0.122 in axial rotation.