Towards a human body model for prediction of vehicle occupant kinematics in omni-directional pre-crash events
In this thesis, a method for activation of the neck and lumbar muscles in an active human body model, based on recorded muscle activity from volunteers, was enhanced and evaluated. The active human body model successfully predicted passenger kinematics in lane change, braking, and combined manoeuvres. As a step towards a model capable of predicting driver kinematics in evasive manoeuvres, the same method was adapted to control the shoulder muscles. The model with active shoulder muscles was evaluated in a simplified test setup. The active model successfully predicted peak elbow displacement for all loading directions.
Based on the results from the included studies, an active muscle controller based on directionally dependent muscle activity data can successfully predict kinematics from reflex response to loading in a finite element human body model. These findings represent an important step towards developing an active human body model able to predict occupant kinematics and muscle forces in omni-directional pre-crash events.
Shoulder Muscle Control
Active Human Body Model
Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet
Active Human Body Model Predictions Compared to Volunteer Response in Experiments with Braking, Lane Change, and Combined Manoeuvres
2019 IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury,; (2019)p. 349-369
Paper i proceeding
Emma Larsson, Jason Fice, Johan Iraeus, Jonas Östh, Bengt Pipkorn, Johan Davidsson. Development of a shoulder muscle feedback controller for human body models
Aktiv humanmodell för prediktering av mänsklig rörelse, steg 4
VINNOVA (2017-05516), 2018-04-01 -- 2021-03-31.
C3SE (Chalmers Centre for Computational Science and Engineering)
Thesis for the degree of Licentiate – Department of Mechanics and Maritime Sciences: 2021:06
Zoom, Password: 568225
Opponent: Prof. Elena Gutierrez Farewik, KTH, Sweden