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This paper presents a technique for developing corridors from individual subject responses contained in experimental biomechanical data sets. Force-deflection response is used as an illustrative example. The technique begins with a method for averaging human subject force-deflection responses in which curve shape characteristics are maintained and discontinuities are avoided. Individual responses sharing a common characteristic shape are averaged based upon normalized deflection values. The normalized average response is then scaled to represent the given data set using the mean peak deflection value associated with the set of experimental data. Finally, a procedure for developing a corridor around the scaled normalized average response is presented using standard deviation calculations for both force and deflection.

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.

Material and structural properties of human tissues under impact loading are needed for the development of physical and computational models used in pedestrian and vehicle occupant protection. Obtaining these global properties directly from the data of biomechanical tests is a challenging task due to nonlinearities of tissue-test setup systems. The objective of this study was to develop subject-specific finite element (FE) techniques for material identification of human tissues using Successive Response Surface Methodology. As example, the test data of a human femur in three-point bending is used to identify parameters of cortical bone. Good global and local predictions of the optimized FE model demonstrate the utility and effectiveness of this new material identification approach.

The objective of this study was to investigate the use of a fiber optic based sensor, ShapeTape, as an instrument for measuring abdominal and chest deflection, and to compare it to the current instrument used in impact biomechanics applications, the chestband. Drift, pressure, and temperature tests were conducted for ShapeTape alone, whereas quasi-static and dynamic loading tests were conducted as comparison tests between the chestband and ShapeTape. The effects of drift and temperature on ShapeTape were very small, averaging 0.26% and 1.2% full scale changes respectively. During the pressure test at a load of 1000 N the ShapeTape sensor tested experience a 7.47% full scale voltage change. The average errors in reporting maximum deflection of the chest form during the quasi-static loading tests were 3.35% and 1.64% for ShapeTape and the chestband respectively.