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Biomechanical data are often assumed to be doubly censored. In this paper, this assumption is evaluated critically for several previously published sets of data. Injury risk functions are compared using simple logistic regression and using survival analysis with 1) the assumption of doubly censored data and 2) the assumption of right-censored (uninjured specimens) and uncensored (injured) data. It is shown that the injury risk functions that result from these differing assumptions are not similar and that some experiments will require a preliminary assessment of data censoring prior to finalizing the experimental design. Some types of data are obviously doubly censored (e.g., chest deflection as a predictor of rib fracture risk), but many types are not left censored since injury is a force-limiting phenomenon (e.g., axial force as a predictor of tibia fracture). Guidelines for determining the censoring for various types of experiment are presented.

Crash test dummies rely on biomechanical data from cadaver studies to biofidelically reproduce loading and predict injury. Unfortunately, it is difficult to obtain equivalent measurements of leg loading in a dummy and a cadaver, particularly for bending moments. A methodology is presented here to implant load cells in the tibia and fibula while minimally altering the functional anatomy of the two bones. The location and orientation of the load cells can be measured in all six degrees of freedom from post-test radiographs. Equations are given to transform tibial and fibular load cell measurements from a cadaver or dummy to a common leg coordinate frame so that test data can be meaningfully compared.