Verification of High-Rate Vertical Loading Laboratory Skeletal Fractures by Comparison with Theater Injury Patterns.

For the current study, an existing theater injury data set was compared to component and whole body experiments meant to replicate the theater high rate vertical loading environment. The theater injury data set was derived from real world events that were within the design range of the Warrior Injury Assessment Manikin. A qualitative and quantitative assessment of the whole body fracture patterns was developed to determine whether the laboratory loading was correctly representing the resulting injuries seen in theater Underbody Blast (UBB) events. Results indicated that most of the experimental test fracture patterns were similar to the theater injuries for Abbreviated Injury Scale body regions of interest (lower extremities, pelvis, and spine); however, some of the body regions had higher similarity scores compared to others. Whole body fracture distribution was less similar than the component tests because of differences in injury distributions. The lower extremity whole body similarity was lower than spine and pelvis similarity. This analysis was able to identify some experimental tests that might not represent theater loading. In conclusion, this analysis confirmed that some laboratory testing produced skeletal injury patterns that are seen in comparable theater UBB events.

A method for developing biomechanical response corridors based on principal component analysis.

The standard method for specifying target responses for human surrogates, such as crash test dummies and human computational models, involves developing a corridor based on the distribution of a set of empirical mechanical responses. These responses are commonly normalized to account for the effects of subject body shape, size, and mass on impact response. Limitations of this method arise from the normalization techniques, which are based on the assumptions that human geometry linearly scales with size and in some cases, on simple mechanical models. To address these limitations, a new method was developed for corridor generation that applies principal component (PC) analysis to align response histories. Rather than use normalization techniques to account for the effects of subject size on impact response, linear regression models are used to model the relationship between PC features and subject characteristics. Corridors are generated using Monte Carlo simulation based on estimated distributions of PC features for each PC. This method is applied to pelvis impact force data from a recent series of lateral impact tests to develop corridor bounds for a group of signals associated with a particular subject size. Comparing to the two most common methods for response normalization, the corridors generated by the new method are narrower and better retain the features in signals that are related to subject size and body shape.

A point-wise normalization method for development of biofidelity response corridors.

An updated technique to develop biofidelity response corridors (BRCs) is presented. BRCs provide a representative range of time-dependent responses from multiple experimental tests of a parameter from multiple biological surrogates (often cadaveric). The study describes an approach for BRC development based on previous research, but that includes two key modifications for application to impact and accelerative loading. First, signal alignment conducted prior to calculation of the BRC considers only the loading portion of the signal, as opposed to the full time history. Second, a point-wise normalization (PWN) technique is introduced to calculate correlation coefficients between signals. The PWN equally weighs all time points within the loading portion of the signals and as such, bypasses aspects of the response that are not controlled by the experimentalist such as internal dynamics of the specimen, and interaction with surrounding structures. An application of the method is presented using previously-published thoracic loading data from 8 lateral sled PMHS tests conducted at 8.9m/s. Using this method, the mean signals showed a peak lateral load of 8.48kN and peak chest acceleration of 86.0g which were similar to previously-published research (8.93kN and 100.0g respectively). The peaks occurred at similar times in the current and previous studies, but were delayed an average of 2.1ms in the updated method. The mean time shifts calculated with the method ranged from 7.5% to 9.5% of the event. The method may be of use in traditional injury biomechanics studies and emerging work on non-horizontal accelerative loading.

External landmark, body surface, and volume data of a mid-sized male in seated and standing postures.

The purpose of this study was to acquire external landmark, undeformed surface, and volume data from a pre-screened individual representing a mid-sized male (height 174.9 cm, weight 78.6 ± 0.77 kg) in the seated and standing postures. The individual matched the 50th percentile value of 15 measures of external anthropometry from previous anthropometric studies with an average deviation of 3%. As part of a related study, a comprehensive full body medical image data set was acquired from the same individual on whom landmark data were collected. Three dimensional bone renderings from this data were used to visually verify the landmark and surface results. A total of 54 landmarks and external surface data were collected using a 7-axis digitizer. A seat buck designed in-house with removable back and seat pan panels enabled collection of undeformed surface contours of the back, buttocks, and posterior thigh. Eight metrics describing the buck positioning are provided. A repeatability study was conducted with three trials to assess intra-observer variability. Total volume and surface area of the seated model were found to be 75.8 × 10(3) cm(3) and 18.6 × 10(3) cm(2) and match the volume and surface area of the standing posture within 1%. Root mean squared error values from the repeatability study were on average 5.9 and 6.6 mm for the seated and standing postures respectively. The peak RMS error as a percentage of the centroid size of the landmark data sets were 3% for both the seated and standing trials. The data were collected as part of a global program on the development of an advanced human body model for blunt injury simulation. In addition, the reported data can be used for many diverse applications of biomechanical research such as ergonomics and morphometrics studies.