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The comfort of seat cushions has become important in many of today's high-performance USAF fighter and tactical aircraft. Experimental investigations have found that there exists a strong relationship between the human subjective discomfort rating for a seat cushion and the pressure distribution on the interface between the cushion and the buttocks. For the analysis of the contact pressure distribution, a finite element model of the human buttock was developed. The model consists of a detailed geometric description of the skin, soft tissues, and bony structures. The development of the model is described in this paper, which includes source data selection, bony structure modeling, joint modeling, soft tissue modeling, and pelvis shape morphing.

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.

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.