Considerable research has shown that there are two mechanisms of blunt injury. One is by crushing the tissue at low velocities of deformation (compression mechanism, C) and the other by a rate-dependent deformation at higher speeds that exceed the energy dissipation of the tissue (viscous mechanism, VC). Analysis of injury causation in experiments must consider both mechanisms. For an impact, there is a peak compression and Viscous response;​ however, it is not possible a priori to determine which mechanism is associated with the injury. Thus, there has been a need to identify the effective velocity separating the two mechanisms of injury.

This study provides new injury tolerances and probability functions for various body and tissue impacts based on injury data related to a compression or viscous mechanism. Six data sets were subjected to statistical analysis to predict injury based on maximum compression and Viscous response of the surrogate or tissue. A set of logistic regression statistics was generated for each data set by repeating the analysis at different levels of velocity. For each data set, goodness of fit was plotted versus velocity and revealed a unique velocity that was most effective in separating the two injury mechanisms. The correlation of VC to the injury became poorer as test data below the transition velocity were added to the statistical analysis.

This new method provides more objectively based tolerance levels of compression and Viscous response and the specific range of deformation velocities for which VC is applicable. Tolerance levels are specified for frontal and lateral impact of the chest and abdomen.