Control-Relevant Design of System Identification Experiments to Improve Behavioral Interventions

This paper presents the design of system identification experiments for physical activity behavioral interventions, utilizing a control-relevant identification test monitoring approach. The goal is to find, in real-time, the shortest possible experiment with sufficient information for identification meeting robust performance conditions. The procedure considers multisinusoidal periodic inputs, and allows modifications on the amplitude and harmonic related frequency content of input signals after each periodic evaluation cycle. The local polynomial method (LPM) is utilized for the computation of transfer function and estimation uncertainties. An improved stopping criterion is formulated relying on robust performance metrics. The procedure is tested through a simulation study relying on a hypothetical system based on a real behavioral intervention.