Active muscle response contributes to increased injury risk of lower extremity in occupant–knee airbag interaction

ABSTRACT

Objective: Recent field data analysis has demonstrated that knee airbags (KABs) can reduce occupant femur and pelvis injuries but may be insufficient to decrease leg injuries in motor vehicle crashes. An enhanced understanding of the associated injury mechanisms requires accurate assessment of physiological-based occupant parameters, some of which are difficult or impossible to obtain from experiments. This study sought to explore how active muscle response can influence the injury risk of lower extremities during KAB deployment using computational biomechanical analysis.

Methods: A full-factorial matrix, consisting of 48 finite element simulations of a 50th percentile occupant human model in a simplified vehicle interior, was designed. The matrix included 32 new cases in combination with 16 previously reported cases. The following influencing factors were taken into account: muscle activation, KAB use, KAB design, pre-impact seating position, and crash mode. Responses of 32 lower extremity muscles during emergency braking were replicated using one-dimensional elements of a Hill-type constitutive model, with the activation level determined from inverse dynamics and validated by existing volunteer tests. Dynamics of unfolding and inflating of the KABs were represented using the state-of-the-art corpuscular particle method. Abbreviated Injury Scale (AIS) 2+ injury risks of the knee–thigh–hip (KTH) complex and the tibia were assessed using axial force and resultant bending moments. With all simulation cases being taken together, a general linear model was used to assess factor significance (P <.05).

Results: As estimated by the regression model across all simulation cases, use of KABs significantly reduced axial femur forces by 4.74 ± 0.43 kN and AIS 2+ injury risk of KTH by 47 ± 6% (P <.05) but did not provide substantial change to injury risk of leg fractures. Muscle activation significantly increased axial force and bending moment of the femur (3.87 ± 0.38 kN and 64.3 ± 5.9 Nm), the tibia (1.49 ± 0.12 kN and 43.0 ± 6.4 Nm), and the resultant probability of AIS 2+ tibia injuries by 36 ± 6% regardless of KAB use and crash scenario. Specifically, when counting on a relative scale, muscle activation exhibited more prominent elevation of injury risk for in-position occupants than out-of-position occupants. In a representative crash scenario—that is, using a bottom-deployed KAB in a nearside oblique impact—muscle bracing of the right leg may lead to 2.6 times higher tibia fracture risk than being relaxed for an out-of-position occupant and 5.4 times higher for an in-position occupant.

Discussion and Conclusions: The mechanism of higher leg injuries in the presence of KAB deployment in real-world crashes can be interpreted by the increased effective body mass, axial compression along the shafts of long bones, and altered pre-impact posture due to muscle contraction. The present analysis suggests that active muscle response can increase the risk of lower extremity injury during occupant–KAB interaction. This study demonstrated the feasibility of advanced human models to investigate the influence of physiologically based parameters on injury outcomes evidenced in field study and insight from computational examination on human variability for development of future restraint systems. Future efforts are recommended on realistic vehicle and restraint environment and advanced modeling strategies toward a full understanding of KAB efficacy.

KEYWORDS:

• Active muscle response
• knee airbag
• lower extremity injury risk
• occupant restraint system
• computational biomechanics

Acknowledgments

The authors thank Dave Schneider and Autoliv ASP, Inc., for their support of this study. We appreciate Dr. Matthew Reed and Dr. Jonathan Rupp at the University of Michigan for sharing technical details about the volunteer sled tests and Dr. Patrick Riley at the University of Virginia for support with OpenSim.

Funding

The data analysis is partly supported by the State Key Laboratory of Automotive Safety and Energy, Tsinghua University, under Grant No. KF16172. The opinions expressed herein are solely those of the authors.