Neck pain is the one of the most frequently reported musculoskeletal complaints. A systematic evaluation of a neck condition may allow clinicians to diagnose possible problems that a subject might have in an objective manner. In this dissertation, we propose a systematic methodology for measuring robustness of the head-neck system that can be used as an objective measure of the head-neck system characteristics. Our method builds on computing the structured singular value μ as a measure of robustness for a particular subject. The μ value is computed under the consideration that the variability of head-neck system model parameters for a tested subject comes from the estimation errors as well as from the natural variation of biological parameters. Both sources of subject's variability determine uncertainty levels that are within some physiologically reasonable ranges. In addition, we analyzed worst-case scenarios of the head-neck system model. The worst-case analysis can provide us with a possible tool to predict what would be the combination of parameters that may cause the worst-case performance. Finally, the design of the robust controller for the head-neck system is also discussed in this dissertation.
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