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An injury risk function defines the probability of an injury as a function of certain measurable or known predictors. In this paper, wavelet analysis is employed for the non-parametric estimation of injury risk functions. After a brief introduction of the wavelet theory, the representation of density function by wavelet series is given. A procedure for the estimation of density function is described. The risk function estimation for right-censored data is investigated by introducing hazard rate function and its wavelet estimator. The use of the developed method is illustrated in a case study, where two sets of data are used: simulation data with known distribution and censoring information, and thoracic impact testing data, which are assumed to be right- censored. Comparisons are made between the wavelet-based approach and the empirical Kaplan-Meier non-parametric method.

The exploration of impact biomechanics via data mining is investigated in this paper. The issues that are particularly pertinent to the use of data miming technology on biomechanics databases are addressed. These issues include (a) relationship between the manikin tests and human tests; (b) extension from lower impact, non-injurious conditions to high impact, injurious conditions; (c) test data versus simulation data; (d) input-output categorization; (e) input-output abstraction and representation; (f) topics for new knowledge discovery; and (g) user scenarios. Technical treatments and considerations are made on the unique characteristics and requirements involved in the biodynamics data mining. They are (a) mixture of classification and numerical prediction; (b) isolated feature space; (c) multiple dependent variables; (d) high dimensionality; (e) algorithm and parameter selection; and (f) scalable data integration and knowledge discovery.

Critical in vehicle crash simulations, human body data sets include mass, moments of inertia (MOIs), and ellipsoid size for each body segment, and location and resistive torque properties for each joint. The Generator of Body Data (GEBOD) program generates these human data sets for use in multibody programs. The objective of this study was to validate GEBOD estimates by directly measuring whole-body inertial properties of 69 volunteers and comparing the results with values calculated by the Articulated Total Body (ATB) model using GEBOD data sets. While the predicted whole-body center of gravity (CG) averaged within 1 cm of the measured values in the horizontal direction, vertically the errors were much larger. The predicted principal MOI were consistently 5%-30% lower than the measured values.

The capability to predictively simulate occupant dynamics in vehicle rollover crashes using the Articulated Total Body (ATB/CVS) model was validated using the results of two controlled automobile rollover crash tests. The ATB model requires the occupant's inertial, geometric, and resistive joint torque properties, the vehicle interior geometry and motion, the contact characteristics for the occupant and vehicle interactions, and the seat belt characteristics. The validation was done by first simulating one test and adjusting the contact and belt properties to obtain good comparison with the test results. Then subsequent tests were simulated using the same properties, but changing only the input vehicle kinematics. Each occupant simulation used the standard Hybrid III data set and measured vehicle interior geometry. The vehicle kinematics were generated by simulating the vehicle dynamics with the ATB model. In one rollover, roof crush significantly affected the occupant's motion.

To demonstrate the Articulated Total Body (ATB) model's capability to predict complex rollover accidents, a rollover accident was selected from the National Accident Sampling System (NASS) and simulated. This paper focuses on the simulation of the vehicle's dynamics which can in turn be used to specify the vehicle motion for occupant simulations. The selected accident case involved a pickup truck, crashing at high speed and completing three rolls. The pickup truck was modeled as a single rigid segment with fifteen contact hyperellipsoids rigidly attached to it. These hyperellipsoids were sized and positioned to approximate the exterior surfaces of the pickup truck. The force-deflection functions were defined based upon previous simulations of rollover tests. The initial conditions were defined to match the data in the NASS accident report as closely as possible.

The objective of this study was to mathematically model several proposed vehicle glazing materials using derived force-deflection characteristics, validate the models' dynamic behavior, and use the resulting glazing models in simulations of occupant dynamics during vehicle rollover. Simulations were performed with the three-dimensional, multibody dynamics program, the Articulated Total Body (ATB) model. The contact characteristics of side windows of tempered glass; polymethyl methacrylimide, also referred to as PMMI; and polycarbonate; as well as windshields from Ford Tempos and Jeeps, were developed from headform impact tests. These characteristics were first validated by performing simulations of the headform impact tests, and were then included in rollover simulations. Previously validated simulations of belted driver and unbelted passenger dynamics during an actual rollover accident were used as the baseline simulations.

Computer simulations of occupant dynamics are ideal for conducting parametric studies evaluating injury countermeasures. A rollover accident was selected from the National Accident Sampling System (NASS) for simulation to validate the Articulated Total Body (ATB) model's capability to predict occupant dynamics during rollover accidents and to gain insight into injury mechanisms. Simulations of both the driver and passenger occupants which may be used in future countermeasure studies are performed. In the selected accident, a pickup truck rolled multiple times, the belted driver had minor injuries and the unrestrained passenger was ejected with fatal injuries. The body properties for both occupants were obtained using the Generator of Body Data (GEBOD) program based on their weights, heights, and sexes. The interior configuration of the vehicle compartment was modeled based on measurements taken from another vehicle of the same model.

Sophisticated computer simulation of human response during various violent force exposure situations requires not only the validated programs, but also high quality databases, especially the data sets that characterize human body structures. Although anthropometric surveys and stereophotometric studies have been performed to create geometric and inertial property databases for the human body, there have been limited efforts on establishing the joint kinematics and resistive torque data sets. This paper presents the development, implementation, and validation of the human articulating joint model parameters for crash dynamics simulations. Measured human joint data on the voluntary range of motion and passive resistive torques were used to mathematically model the shoulder, elbow, hip, knee, and ankle joints.