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The widespread implementation of air bags has increased the incidence of upper extremity injuries in the automotive crash environment. The first step in reducing these injuries is to determine applicable upper extremity injury criteria. The purpose of this paper is to develop injury risk functions for the fifth percentile female forearm, humerus, wrist, and elbow. Injury tolerance data for each anatomical region were gathered from experiments with controlled impact loading of disarticulated small female cadaver upper extremities. This technique allowed for the applied load to be directly quantified. All data were mass scaled to the fifth percentile female. In order to develop the risk functions, the logit distribution was integrated for the uncensored data, while logistic regression and generalized estimating equations statistical analysis techniques were used for censored data.

As accurate measuring of head accelerations is an important aspect in predicting head injury, it is important that the measuring sensor be well-coupled to the head. Various sensors and sensor mounting schemes have been attempted in the past with varying results. This study uses a small, implantable acceleration sensor pack in the ear to study impact coupling with the human skull. The output from these ear-mounted accelerometers is compared to laboratory reference accelerometers rigidly attached to the skull of two cadaveric head specimens for both low-amplitude oscillatory tests and high-amplitude impact drop tests. The combination of sensor type and mounting scheme demonstrates the feasibility of using ear mounted sensors to predict head acceleration response. Previously reported progressive phase lag was not seen in this study, with the comparison between ear mounted accelerometers and rigidly mounted head accelerometers ranging from very good to excellent.