Event

Welcome to I Putu Alit Putra's doctoral dissertation! He will defend his doctoral thesis "Occupant Neck Muscle Modelling in Rear-End Crashes".

I Putu Alit Putra is a Ph.D student at the Injury Prevention Group, Department of Mechanics and Maritime Sciences, Division of Vehicle Safety. He focuses his research on human body computational modeling, specifically in the field of active neck muscles modeling for the female occupant model. The goal of his research is to develop validated neck muscles model for the female occupant model and to evaluate the effects of neck muscles contraction to the whiplash injury during rear-end car collision.

• Opponent: Professor Duane Cronin, Ph.D., PEng, Tier 1 Canada Research Chair in Trauma Biomechanics and Injury Prevention (tBIP), Director of the Impact Mechanics and Material Characterization (IMMC) Lab, Mechanical And Mechatronics Engineering, University of Waterloo, Canada
• Supervisors: Robert Thomson (Professor, Chalmers) & Johan Iraeus (Chalmers
• Examiner: Mats Svensson (Professor, Chalmers)

Summary

Injuries in the neck, commonly known as whiplash injuries or Whiplash Associated Disorders (WAD), are prevalent worldwide. Whiplash injuries are most often reported in low-speed rear-end car crashes. Women have been shown to have a higher risk of experiencing whiplash injuries than men. However, there is no firm conclusion of why women tend to have a higher susceptibility to whiplash injuries than men. During low-speed rear-end crashes, our reflex mechanisms trigger muscle activity in the neck. Due to their significant volume, neck muscles could influence the risk of whiplash injuries. How muscles affect the risk of whiplash injuries is still unclear and not fully understood. Reflex mechanisms were investigated in the present thesis to better understand how neck muscle responses influence whiplash injuries. A computer model was developed to represent an average female with neck muscle responses. This knowledge was even implemented in an average male computer model. Based on the collective studies in this thesis, it was found that the developed models can replicate the head and neck motion of female (and even male) occupants during low-speed rear-end car crashes. Whiplash injury prediction could be more reliable using these models. Consequently, the results of this research can provide clues to understand why women have a higher risk in whiplash injuries than males.