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.
spatial tuning patterns
human body models
Building Saga, room Alfa, Hörselgången 4, Göteborg
Opponent: Associate Professor Anita Vasavada, The Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, USA.