Muscle Responses in Dynamic Events. Volunteer experiments and numerical modelling for the advancement of human body models for vehicle safety assessment.

Doctoral thesis, 2017

Fatalities and injuries to car occupants in motor vehicle crashes continue to be a serious global socio-economic issue. Advanced safety systems that provide improved occupant protection and crash mitigation have the potential to reduce this burden. For the development and virtual assessment of these systems, numerical human body models (HBMs) that predict occupant responses have been developed. Currently, there is a need for increasing the level of biofidelity in these models to facilitate simulation of occupant responses influenced by muscle contraction, such as often experienced during pre-crash vehicle manoeuvres. The aim of this thesis was to provide data and modelling approaches for the advancement of HBMs capable of simulating occupant responses in a wide range of pre-crash scenarios. Volunteer experiments were conducted to study driver and passenger responses during emergency braking with a standard seatbelt and with a seatbelt equipped with a reversible pre-tensioner. Muscle activity, kinematic, and boundary condition data were collected. The data showed that pre-tensioning the seatbelt prior to braking influenced the muscular and kinematic responses of occupants. Drivers modified their responses during voluntary braking, resulting in different kinematics than were observed during autonomous braking. Passenger and driver responses also differed during autonomous braking. The findings demonstrate that HBMs need to account for the differences in postural responses between occupant roles as well as the adjustments made by drivers during voluntary braking. The studies provide detailed data sets that can be used for model tuning and validation. The modelling efforts of this work focused on simulation of head-neck responses. To facilitate the modelling of neck muscle recruitment, muscle activity data from volunteers exposed to multi-directional horizontal seated perturbations were analysed. The derived spatial tuning curves revealed muscle- and direction-specific recruitment patterns. The experimental tuning curves can be used as input to models or to verify spatial tuning of muscle recruitment in HBMs. A method for simulating muscle recruitment of individual neck muscles was developed. The approach included a combination of head kinematics and muscle length feedback to generate muscle specific activation levels. The experimental tuning curves were used to define appropriate sets of muscle activation in response to head kinematics feedback. The predicted spatial tuning using the two feedback loops was verified in multi-directional horizontal gravity simulations. The results showed that muscle activation generated by individual or combined feedback loops influenced the predicted head and intervertebral kinematics. The developed method has the potential to improve prediction of omnidirectional head and neck responses with HBMs. However, further work is needed to verify these findings. Overall, this research has increased knowledge about the muscle responses of occupants in dynamic events typical of pre-crash scenarios. The findings highlight important aspects that must be considered to enable active HBMs to capture a wide range of occupant responses. The data presented support the advancement of current and future HBMs, which will contribute to the development of improved safety systems that reduce the number of fatalities and injuries in motor vehicle crashes.