New Risk Curves for NHTSA's Brain Injury Criterion (BrIC): Derivations and Assessments.

The National Highway Traffic Safety Administration (NHTSA) recently published a Request for Comments regarding a potential upgrade to the US New Car Assessment Program (US NCAP) - a star-rating program pertaining to vehicle crashworthiness. Therein, NHTSA (a) cited two metrics for assessing head risk: Head Injury Criterion (HIC15) and Brain Injury Criterion (BrIC), and (b) proposed to conduct risk assessment via its risk curves for those metrics, but did not prescribe a specific method for applying them. Recent studies, however, have indicated that the NHTSA risk curves for BrIC significantly overstate field-based head injury rates. Therefore, in the present three-part study, a new set of BrIC-based risk curves was derived, an overarching head risk equation involving risk curves for both BrIC and HIC15 was assessed, and some additional candidatepredictor- variable assessments were conducted. Part 1 pertained to the derivation. Specifically, data were pooled from various sources: Navy volunteers, amateur boxers, professional football players, simple-fall subjects, and racecar drivers. In total, there were 4,501 cases, with brain injury reported in 63. Injury outcomes were approximated on the Abbreviated Injury Scale (AIS). The statistical analysis was conducted subject to ordinal logistic regression analysis (OLR), such that the various levels of brain injury were cast as a function of BrIC. The resulting risk curves, with Goodman Kruksal Gamma=0.83, were significantly different than those from NHTSA. Part 2 pertained to the assessment relative to field data. Two perspectives were considered: "aggregate" (ΔV=0-56 km/h) and "point" (high-speed, regulatory focus). For the aggregate perspective, the new risk curves for BrIC were applied in field models pertaining to belted, mid-size, adult drivers in 11-1 o'clock, full-engagement frontal crashes in the National Automotive Sampling System (NASS, 1993-2014 calendar years). For the point perspective, BrIC data from tests were used. The assessments were conducted for minor, moderate, and serious injury levels for both Newer Vehicles (airbag-fitted) and Older Vehicles (not airbag-fitted). Curve-based injury rates and NASS-based injury rates were compared via average percent difference (AvgPctDiff). The new risk curves demonstrated significantly better fidelity than those from NHTSA. For example, for the aggregate perspective (n=12 assessments), the results were as follows: AvgPctDiff (present risk curves) = +67 versus AvgPctDiff (NHTSA risk curves) = +9378. Part 2 also contained a more comprehensive assessment. Specifically, BrIC-based risk curves were used to estimate brain-related injury probabilities, HIC15-based risk curves from NHTSA were used to estimate bone/other injury probabilities, and the maximum of the two resulting probabilities was used to represent the attendant headinjury probabilities. (Those HIC15-based risk curves yielded AvgPctDiff=+85 for that application.) Subject to the resulting 21 assessments, similar results were observed: AvgPctDiff (present risk curves) = +42 versus AvgPctDiff (NHTSA risk curves) = +5783. Therefore, based on the results from Part 2, if the existing BrIC metric is to be applied by NHTSA in vehicle assessment, we recommend that the corresponding risk curves derived in the present study be considered. Part 3 pertained to the assessment of various other candidate brain-injury metrics. Specifically, Parts 1 and 2 were revisited for HIC15, translation acceleration (TA), rotational acceleration (RA), rotational velocity (RV), and a different rotational brain injury criterion from NHTSA (BRIC). The rank-ordered results for the 21 assessments for each metric were as follows: RA, HIC15, BRIC, TA, BrIC, and RV. Therefore, of the six studied sets of OLR-based risk curves, the set for rotational acceleration demonstrated the best performance relative to NASS.

Influence of fatigue time and level on increases in postural sway.

The purpose of this study was to investigate the influence of fatigue time and fatigue level on the increases in postural sway during quiet standing. Centre of pressure-based measures of postural sway were collected both before and after fatiguing participants using three different fatigue levels and two different fatigue times. Results showed increasing fatigue time increased sway velocity and sway area, and increasing fatigue level increased sway velocity. Fatigue time effects are important to consider when applying laboratory-based findings to the field given that the fatigue time can differ substantially between the two. Fatigue level effects imply a dose - response relationship between localized muscle fatigue and risk of falling that can have important implications in work/rest cycle scheduling for occupations at risk of injurious falls.

Lumbar extensor fatigue and circumferential ankle pressure impair ankle joint motion sense.

Fatigue of the lumbar extensor muscles has been associated with a degradation of balance, but the mechanism is not well understood. The ankle plays a major role in upright standing, and loss of proprioceptive acuity at the ankle could contribute to a degradation of balance. Therefore, the first objective of this study was to investigate the effect of lumbar extensor fatigue on ankle proprioceptive acuity. The second objective was to investigate the effect of circumferential ankle pressure (CAP) on ankle proprioceptive acuity to evaluate CAP as a potential intervention to mitigate any loss of proprioceptive acuity at the ankle with lumbar extensor fatigue. To address these objectives, ankle joint motion sense was evaluated with and without CAP, both before and after the lumbar extensors were fatigued. Results showed an impairment in joint motion sense with both fatigue and CAP. These results indicate that lumbar extensor fatigue impairs ankle proprioceptive acuity, which may help explain observed increases in postural sway subsequent to lumbar extensor fatigue.